Fraunhofer USA Center for Sustainable Energy Systems

5 Channel Center Street, Boston, MA 02210

Fraunhofer USA Center for Sustainable Energy Systems

ENERGY CONSUMPTION OF CONSUMER ELECTRONICS 

IN U.S. HOMES IN 2013

FINAL REPORT TO THE CONSUMER ELECTRONICS ASSOCIATION (CEA®)

June 2014

by Bryan Urban, Victoria Shmakova, Brian Lim, and Kurt Roth

PI

Dr. Kurt Roth, Building Energy Efficiency Group Leader 

kroth@fraunhofer.org 617 575-7256
Fraunhofer USA Center for Sustainable Energy Systems 2

Disclaimer

This report was commissioned by the Consumer Electronics Association on terms specifically limiting 

Fraunhofer USA’s liability. Our conclusions are the results of the exercise of our best professional 

judgment, based in part upon materials and information provided to us by the Consumer Electronics 

Association and others. Use of this report by any third party for whatever purposes should not, and does 

not, absolve such third party from using due diligence in verifying the report’s contents.

Any use which a third party makes of this document, or any reliance on it, or decisions to be made based 

on it, are the responsibility of such third party. Fraunhofer USA accepts no duty of care or liability of any 

kind whatsoever to any such third party, and no responsibility for damages, if any, suffered by any third 

party as a result of decisions made, or not made, or actions taken, or not taken, based on this document.

This report may be reproduced only in its entirety, and may be distributed to third parties only with the 

prior written consent of the Consumer Electronics Association.
Fraunhofer USA Center for Sustainable Energy Systems 3

Table of Contents

List of Figures...........................................................................................................................................................................5

List of Tables ............................................................................................................................................................................7

List of Acronyms and Abbreviations .........................................................................................................................................9

Acknowledgements................................................................................................................................................................10

Executive Summary................................................................................................................................................................11

1 Introduction ...............................................................................................................................................................14

1.1 Approach............................................................................................................................................................................ 14

1.2 Report Organization........................................................................................................................................................... 14

2 Energy Consumption Calculation Methodology ..........................................................................................................15

2.1 Residential Installed Base................................................................................................................................................... 15

2.2 Power Draw by Mode ........................................................................................................................................................ 15

2.3 Annual Usage by Mode ...................................................................................................................................................... 16

3 Energy Consumption of Consumer Electronics in U.S. Homes .....................................................................................17

3.1 Summary ............................................................................................................................................................................ 17

3.2 Devices Selected for Further Analysis................................................................................................................................ 19

3.3 Computer Speakers............................................................................................................................................................ 20

3.3.1 Current Energy Consumption ...................................................................................................................................... 20

3.3.2 Comparison with Prior Energy Consumption Estimates .............................................................................................. 23

3.3.3 References................................................................................................................................................................... 23

3.4 Desktop Computers............................................................................................................................................................ 24

3.4.1 Current Energy Consumption ...................................................................................................................................... 24

3.4.2 Comparison with Prior Energy Consumption Estimates .............................................................................................. 31

3.4.3 References................................................................................................................................................................... 32

3.5 Portable Computers........................................................................................................................................................... 34

3.5.1 Current Energy Consumption ...................................................................................................................................... 34

3.5.2 Comparison with Prior Energy Consumption Estimates .............................................................................................. 42

3.5.3 References................................................................................................................................................................... 43

3.6 Home Audio: Shelf/Compact Audio and Speaker Docks.................................................................................................... 45

3.6.1 Current Energy Consumption ...................................................................................................................................... 45

3.6.2 Comparison with Prior Energy Consumption Estimates .............................................................................................. 49

3.6.3 References................................................................................................................................................................... 50

3.7 Monitors............................................................................................................................................................................. 51

3.7.1 Current Energy Consumption ...................................................................................................................................... 51

3.7.2 Comparison with Prior Energy Consumption Estimates .............................................................................................. 56

3.7.3 References................................................................................................................................................................... 57

3.8 Network Equipment........................................................................................................................................................... 58

3.8.1 Current Energy Consumption ...................................................................................................................................... 58

3.8.2 Comparison with Prior Energy Consumption Estimates .............................................................................................. 62

3.8.3 References................................................................................................................................................................... 63

3.9 Smart Phones..................................................................................................................................................................... 65

3.9.1 Current Energy Consumption ...................................................................................................................................... 65

3.9.2 Comparison with Prior Energy Consumption Estimates .............................................................................................. 68

3.9.3 References................................................................................................................................................................... 68

3.10 Tablet Computers............................................................................................................................................................... 70

3.10.1 Current Energy Consumption ...................................................................................................................................... 70

3.10.2 Comparison with Prior Energy Consumption Estimates .............................................................................................. 74

3.10.3 References................................................................................................................................................................... 74

3.11 Set-top Boxes..................................................................................................................................................................... 76

3.11.1 Current Energy Consumption ...................................................................................................................................... 76

3.11.2 Comparison with Prior Energy Consumption Estimates .............................................................................................. 84

3.11.3 References................................................................................................................................................................... 86

3.12 Televisions.......................................................................................................................................................................... 88

3.12.1 Current Energy Consumption ...................................................................................................................................... 88

3.12.2 Comparison with Prior Energy Consumption Estimates .............................................................................................. 95

3.12.3 References................................................................................................................................................................... 96

3.13 Video Game Systems.......................................................................................................................................................... 98

3.13.1 Current Energy Consumption ...................................................................................................................................... 98
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3.13.2 Comparison with Prior Energy Consumption Estimates ............................................................................................ 103

3.13.3 References................................................................................................................................................................. 105

3.14 Other Devices................................................................................................................................................................... 106

3.14.1 References................................................................................................................................................................. 112

4 Conclusions..............................................................................................................................................................115

4.1 Key Trends........................................................................................................................................................................ 118

4.1.1 Televisions ................................................................................................................................................................. 118

4.1.2 Computers ................................................................................................................................................................. 119

4.2 References ....................................................................................................................................................................... 120

Appendix A – CE Usage Surveys............................................................................................................................................121

A.1 Personal Computers (Desktops and Portables) ...................................................................................................................... 121

A.2 Home Audio............................................................................................................................................................................ 123

A.3 Mobile Devices (Smartphones and Tablets) ........................................................................................................................... 125

A.4 Televisions.............................................................................................................................................................................. 126

A.5 Video Game Consoles............................................................................................................................................................. 131

Appendix B – Energy and Usage Models...............................................................................................................................135

B.1 Energy Models — Personal Computers (Desktops and Portables) ......................................................................................... 135

B.1.1 Plugged-In Install Base ............................................................................................................................................... 135

B.1.2 Operational Modes.................................................................................................................................................... 136

B.1.2.1 Operational Modes for External Power Supplies of Portable PCs.............................................................................. 136

B.1.3 Usage Modeling ......................................................................................................................................................... 137

B.1.3.1 Day Periods................................................................................................................................................................ 137

B.1.3.1.1 Sample Energy Consumption across Daytime Periods............................................................................................... 138

B.1.3.2 Daytime Periods......................................................................................................................................................... 139

B.1.3.3 Usage Session ............................................................................................................................................................ 139

B.1.3.4 Post-Session............................................................................................................................................................... 140

B.1.3.4.1 Manual Power Management Routines...................................................................................................................... 140

B.1.3.4.2 Automated Power Management Settings Modes...................................................................................................... 141

B.1.3.4.3 Usage Time by Operational Mode in Post-Session .................................................................................................... 141

B.1.3.5 Non-Session ............................................................................................................................................................... 141

B.1.3.6 Total Usage by Operational Mode in Daytime Period ............................................................................................... 142

B.1.4 Pre-Evening Period .................................................................................................................................................... 142

B.1.5 Evening Period ........................................................................................................................................................... 142

B.1.6 Night Period............................................................................................................................................................... 142

B.1.7 Whole Day ................................................................................................................................................................. 143

B.1.7.1 Desktop PC................................................................................................................................................................. 143

B.1.7.2 Portable PCs............................................................................................................................................................... 143

B.1.8 References................................................................................................................................................................. 144

B.2 Energy Usage Models — Mobile Devices (Tablets and Smartphones)............................................................................. 145

B.2.1 Plugged-In Install Base ............................................................................................................................................... 145

B.2.2 Energy Consumption.................................................................................................................................................. 145

B.2.2.1 Charging..................................................................................................................................................................... 146

B.2.2.2 Usage ......................................................................................................................................................................... 147

B.2.2.3 Idle ............................................................................................................................................................................. 147

B.2.2.4 Unplugged.................................................................................................................................................................. 147

B.2.2.5 Representative Weights for Mobile Device and Charger Models.............................................................................. 148

B.2.2.6 Whole Day Energy Consumption ............................................................................................................................... 151

B.2.3 References................................................................................................................................................................. 151

B.3 Video Game Consoles............................................................................................................................................................. 154

B.3.1 Installed Base............................................................................................................................................................. 154

B.3.2 Usage of video game consoles including 8th generation models............................................................................... 154

B.3.3 Power Draw ............................................................................................................................................................... 155

B.3.4 Usage estimates – Video Game Consoles.................................................................................................................. 156

B.3.4.1 Calculations of Time Spent in Operational Modes..................................................................................................... 156

B.3.5 References................................................................................................................................................................. 157

B.4 Home Audio ..................................................................................................................................................................... 158

B.4.1 Speaker Docks............................................................................................................................................................ 158

B.4.2 Shelf Stereo Systems.................................................................................................................................................. 158
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List of Figures

Figure ES-1: Residential CE annual electricity consumption by category. ...................................................................................... 12

Figure ES-2: Residential CE annual electricity consumption by device. .......................................................................................... 12

Figure ES-3: Annual unit electricity consumption for categories evaluated in detail. .................................................................... 13

Figure 2-1: UEC and AEC calculation methodology (ADL 2002). ..................................................................................................... 15

Figure 3-1 : UEC, installed base, and AEC of CE categories evaluated in detail. ............................................................................. 18

Figure 3-2: Distribution of computer speaker systems per desktop and portable computer......................................................... 20

Figure 3-3: Unit Energy Consumption by mode and Annual Energy Consumption by computer speaker system type. ................ 22

Figure 3-4: Distribution of households with numbers of desktop PCs plugged in during the past month (Nov 2013)................... 25

Figure 3-5: Representative power draw by mode of tower and AIO desktop PCs.......................................................................... 27

Figure 3-6: Average per session usage duration and number of sessions “yesterday” for primary and secondary desktop PCs... 28

Figure 3-7: Total usage duration “yesterday” for primary and secondary desktop PCs. ................................................................ 28

Figure 3-8: Likelihood of users manually setting desktop PCs into various modes for the daytime or night. ................................ 29

Figure 3-9: Percentage of desktop PCs with different automatic PM modes enabled. .................................................................. 29

Figure 3-10: Average time spent in various operational modes in one day and in one year for desktop PCs. Weighted average 

across primary and secondary tower and AIO desktop PCs............................................................................................................ 30

Figure 3-11: Total energy consumed in various operational modes in one day and in one year for desktop PCs. Weighted 

average across primary and secondary tower and AIO desktop PCs. ............................................................................................. 31

Figure 3-12: Distribution of households by number of portable PCs owned or plugged-in during the past month (Nov. 2013). .. 34

Figure 3-13: Representative power draw by mode of notebook and netbook portable PCs. ........................................................ 37

Figure 3-14: Average per session usage and number of sessions “yesterday” for primary and secondary portable PCs............... 38

Figure 3-15: Average total usage “yesterday” for primary and secondary portable PCs................................................................ 38

Figure 3-16: Portion of users manually setting portable PCs into various power modes for the daytime or nighttime. ............... 39

Figure 3-17: Percentage of portable PCs with various automatic PM modes enabled................................................................... 39

Figure 3-18: Average time spent in various operational modes in one day (left) and in one year (right) for portable PCs............ 41

Figure 3-19: Total energy consumed in various operational modes in one day and in one year for portable PCs. Weighted 

average across primary and secondary notebook and netbook portable PCs................................................................................ 42

Figure 3-20: Example of a speaker dock (left), and shelf stereo system (right), source: iHome, Sony. .......................................... 45

Figure 3-21: Active power draws of different mini-shelf stereo systems (Fraunhofer measurements). ........................................ 47

Figure 3-22: Frequencies of responses regarding the active daily usage of speaker systems. ....................................................... 48

Figure 3-23: Speaker dock UEC distribution among different modes............................................................................................. 49

Figure 3-24: Installed base of monitors and computers. ................................................................................................................ 51

Figure 3-25: Distribution of monitors per desktop and portable computer. .................................................................................. 52

Figure 3-26: Distribution of LCD monitors installed base in 2013 by diagonal screen size (FhCSE 2011, DisplaySearch 2014)...... 52

Figure 3-27: Portion of monitor sales by backlight technology (DisplaySearch 2014).................................................................... 53

Figure 3-28: Active-mode power draw measurements for ENERGY STAR LCD monitors by backlight technology (EPA 2013). ..... 54

Figure 3-29: Decision diagram for determining monitor operational mode................................................................................... 55

Figure 3-30: Portion of households with broadband Internet subscriptions and home networks (CEA 2013b). ........................... 58

Figure 3-31: Type of Internet service at home (CEA 2013a). .......................................................................................................... 60

Figure 3-32: AEC for small network equipment.............................................................................................................................. 62

Figure 3-33: U.S. broadband household subscribers by technology type (LBNL 2010, TIA 2013, CEA 2013a)................................ 63

Figure 3-34: Distribution of households with smartphones used during the past month (Nov. 2013) vs. Ownership (Feb. 2013, 

CEA 2013)........................................................................................................................................................................................ 65

Figure 3-35: Energy consumption of smartphones in different operational modes....................................................................... 68

Figure 3-36: Percentage of households with tablets used during the past month (Nov. 2013) vs. Ownership (Feb. 2013) (CEA 

2013)............................................................................................................................................................................................... 70

Figure 3-37: Energy consumption of tablets in different operational modes................................................................................. 74

Figure 3-38: Power draw of subscription set-top boxes by provider type and selected features, n=84 (EPA 2012). ..................... 81

Figure 3-39: Summary of installed base, UEC and AEC for STBs. .................................................................................................... 83

Figure 3-40: Annual STB sales to dealers by display technology..................................................................................................... 86
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Figure 3-41: Cumulative STB sales to dealers by display technology since 2005............................................................................ 86

Figure 3-42: TV ownership distribution (CE Usage Survey)............................................................................................................. 88

Figure 3-43: Screen size for LCD and Plasma TVs from 2010 to 2012. Reclassifying survey responses for Plasma TVs of 37 in. or 

lower as LCD TVs improves surveyagreement with sales data. ...................................................................................................... 89

Table 3-69: Distribution of TVs by display type. Figure 3-44: TVs by display type. .................................................................... 90

Figure 3-45: TVs by screen size and age (Nov. 2013 survey). Bin ranges not of equal size............................................................. 90

Figure 3-46: Distribution of TVs by display technology and usage priority..................................................................................... 91

Figure 3-47: Power regressions for LCD and Plasma TVs (CEC 2013).............................................................................................. 92

Figure 3-48: Impact of TV brightness on power draw (EPA 2013). ................................................................................................. 93

Figure 3-49: TV unit energy consumption by usage priority and display type................................................................................ 94

Figure 3-50: Active and off mode AEC by TV priority and display type........................................................................................... 95

Figure 3-51: Annual TV sales to dealers by display technology (CEA 2013, 2010).......................................................................... 96

Figure 3-52: Cumulative TV sales to dealers by display technology since 1999 (CEA 2013, 2010). ................................................ 96

Figure 3-53: Fraction of video game systems installed in U.S. homes by platform. ....................................................................... 99

Figure 3-54: Turned ON and actively used hours/day for different video game console platforms............................................. 101

Figure 3-55: Distribution of active usage among gaming and video (streaming and playback) by platform................................ 102

Figure 3-56: Video game console UEC and usage by mode. ......................................................................................................... 102

Figure 3-57: Annual Energy Consumption by different video game consoles .............................................................................. 103

Figure 3-58: Historical active-gaming mode power draw values for video game systems (Calland 2014, Jessop 2014, Boxleitner 

2014, NRDC 2010)......................................................................................................................................................................... 104

Figure 3-59: UEC, installed base, and AEC of other CE devices evaluated in less detail. .............................................................. 107

Figure 4-1: Residential electricity consumption in 2013 by major end uses (DOE 2012, Current Study). .................................... 115

Figure 4-2: Residential primary energy consumption in 2013 by major end uses (DOE 2012, Current Study)............................. 116

Figure 4-3: Residential CE electricity consumption by category. .................................................................................................. 116

Figure 4-4: Unit electricity consumption for the CE categories evaluated in detail...................................................................... 117

Figure 4-5: AEC by operational mode for the categories evaluated in detail. .............................................................................. 117

Figure 4-6: Breakdown of UEC by operational modes for the categories evaluated in detail. ..................................................... 118
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List of Tables

Table ES-1: Consumer electronics analyzed in further detail. ........................................................................................................ 11

Table 3-1: Residential CE energy consumption summary............................................................................................................... 17

Table 3-2: CE analyzed in the current study. .................................................................................................................................. 19

Table 3-3: Installed base of computer speaker systems (CE Usage Survey). .................................................................................. 21

Table 3-4: Power draw by mode for computer speaker systems. .................................................................................................. 22

Table 3-5: Annual usage by mode of computer speaker systems (hours/year).............................................................................. 22

Table 3-6: UEC and AEC calculation for computer speaker systems............................................................................................... 23

Table 3-7: Prior energy consumption estimates for computer speaker systems............................................................................ 23

Table 3-8 : Installed base estimates for desktop PCs from different data sources......................................................................... 24

Table 3-9: Plugged-In installed base estimates for Tower and All-in-One (AIO) Desktop Computers from CE Usage Survey. ....... 24

Table 3-10: Plugged-In installed base estimate for All-in-One Desktop Computers based on sales via consumer channels 

(DisplaySearch 2014). ..................................................................................................................................................................... 25

Table 3-11: Power draw estimates for desktop computers from different data sources. .............................................................. 26

Table 3-12: Estimated desktop PC installed base by computer vintage to evaluate relative power draw characteristics derived 

from Figure 3 of (CEA 2014). Average age: 3.2 years...................................................................................................................... 26

Table 3-13: Comparison of percentage of time desktop PCs spent in various operational modes with other data sources. ........ 30

Table 3-14: UEC and AEC values for desktop PCs. .......................................................................................................................... 31

Table 3-15: Current and prior energy consumption estimates for desktop PCs. ............................................................................ 32

Table 3-16: Installed base estimates for portable PCs from different data sources. ...................................................................... 34

Table 3-17: Plugged-In installed base estimates for notebook and netbook portable PCs from the CE Usage Survey. ................. 35

Table 3-18: Power draw estimates for portable PCs from different data sources.......................................................................... 35

Table 3-19: Determining relative power draw characteristics from age of portable PCs owned in Dec. 2013 derived from Figure 3 

of (CEA 2014). Average age: 2.4 years. ........................................................................................................................................... 36

Table 3-20: Power draw estimates of the external power supply for portable PCs (DOE 2012), weighted by shipment 

distribution. This excludes the power draw due to the portable PC. ............................................................................................. 36

Table 3-21: Time usage estimates of portable PC EPSs from DOE (2012). Weighted average by shipment distribution of the 

reference case. ............................................................................................................................................................................... 40

Table 3-22: Comparison of percentage of time notebook PCs spent in various operational modes with other data sources. ...... 41

Table 3-23: Unit energy consumption (UEC), installed base, and annual energy consumption (AEC) of portable PCs. ................. 42

Table 3-24: Current and prior energy consumption estimates for portable PCs. ........................................................................... 43

Table 3-25: Installed base of speaker docks and shelf stereo systems (CE Usage Survey). ............................................................ 45

Table 3-26: Power draw by mode for audio systems...................................................................................................................... 47

Table 3-27: Annual usage by mode of speaker dock and shelf stereo systems.............................................................................. 48

Table 3-28: UEC calculation for speaker systems. .......................................................................................................................... 49

Table 3-29: AEC summary for speaker systems. ............................................................................................................................. 49

Table 3-30: Prior energy consumption estimates for speaker docks.............................................................................................. 50

Table 3-31: Prior energy consumption estimates for mini-shelf stereo system. ............................................................................ 50

Table 3-32: Installed base of monitors............................................................................................................................................ 51

Table 3-33: Average power draw estimates for monitors. ............................................................................................................. 54

Table 3-34: Daily usage of monitors by mode. ............................................................................................................................... 55

Table 3-35: UEC and AEC estimates for monitors........................................................................................................................... 56

Table 3-36: Prior energy consumption estimates for monitors. ..................................................................................................... 56

Table 3-37: Installed base of network devices (LBNL 2010, CEA 2013a, NRDC 2013)..................................................................... 59

Table 3-38: Power draws for network equipment (NRDC 2013, EPA 2013b) ................................................................................. 61

Table 3-39: UEC and AEC calculations for network equipment. ..................................................................................................... 62

Table 3-40: Prior energy consumption estimates for broadband access devices (modems and IADs)........................................... 63

Table 3-41: Prior energy consumption estimates for routers and other devices (non-modem) .................................................... 63

Table 3-42: Installed base estimates for smartphones from different data sources. ..................................................................... 65

Table 3-43: Plugged-In installed base estimates for smartphones from the CE Usage Survey....................................................... 66
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Table 3-44: Representative battery capacity for smartphones, and power draw estimates for original and other chargers. ....... 66

Table 3-45: Energy consumption estimates due to charging smartphones.................................................................................... 66

Table 3-46: Energy consumption estimates due to smartphones being plugged into chargers after being fully charged (idle). ... 67

Table 3-47: Energy consumption estimate for smartphones in unplugged mode.......................................................................... 67

Table 3-48: UEC and AEC values for smartphones.......................................................................................................................... 68

Table 3-49: Current and prior energy consumption estimates for smartphones. .......................................................................... 68

Table 3-50: Recent installed base estimates for tablets. ................................................................................................................ 70

Table 3-51: Plugged-In installed base estimates for tablets from the CE Usage Survey. ................................................................ 71

Table 3-52: Representative capacity and efficiency of original and aftermarket batteries and chargers for tablets. .................... 72

Table 3-53: Energy consumption estimates due to charging tablets.............................................................................................. 72

Table 3-54: Energy consumption estimates of tablets in idle mode............................................................................................... 73

Table 3-55: Energy consumption estimate for tablets in unplugged mode.................................................................................... 73

Table 3-56: UEC and AEC values for tablets.................................................................................................................................... 74

Table 3-57: Current and prior energy consumption estimates for tablets. .................................................................................... 74

Table 3-58: Pay TV customers by service, millions.......................................................................................................................... 77

Table 3-59: Installed base of pay TV STBs by service (Nov. 2013 survey). ...................................................................................... 77

Table 3-60: Installed base of pay TV STBs, millions......................................................................................................................... 78

Table 3-61: Subscribers with multi-room STBs, millions (Nov. 2013 survey).................................................................................. 79

Table 3-62: Cumulative STB shipment projections from Q2-2010 to Q4-2013 (DOE 2013a).......................................................... 79

Table 3-63: Installed base of standalone STBs, millions.................................................................................................................. 80

Table 3-64: Power draw and installed base by device. ................................................................................................................... 82

Table 3-65: UEC and AEC summary for STBs................................................................................................................................... 84

Table 3-66: Prior energy consumption estimates for subscription STBs......................................................................................... 85

Table 3-67: Prior energy consumption estimates for standalone STBs. ......................................................................................... 85

Table 3-68: Installed base estimates for TVs in 2013...................................................................................................................... 88

Table 3-69: Distribution of TVs by display type. Figure 3-44: TVs by display type. .................................................................... 90

Table 3-70: ENERGY STAR power draw requirements for TVs. ....................................................................................................... 91

Table 3-71: Active mode power regressions by TV screen area, display, and production year. ..................................................... 92

Table 3-72: UEC and AEC calculations for TVs for 2013.................................................................................................................. 94

Table 3-73: Prior energy consumption estimates for TVs............................................................................................................... 95

Table 3-74: Installed base of video game consoles......................................................................................................................... 98

Table 3-75: Installed base and power draw by mode of video game systems.............................................................................. 100

Table 3-76: Usage by different video game consoles (CE Usage Survey)...................................................................................... 101

Table 3-77: Annual hours by mode for video game consoles for LBNL 2013, FhCSE 2011 and current study.............................. 101

Table 3-78: Comparison of different estimates for the portion of active time in gaming and other modes................................ 101

Table 3-79: UEC calculation for video game systems.................................................................................................................... 102

Table 3-80: AEC summary for video game systems...................................................................................................................... 103

Table 3-81: Prior energy consumption estimates for video game systems. ................................................................................. 103

Table 3-82: UEC and installed base estimates for other products................................................................................................ 106

Table 3-83: Average power draw by mode estimates for other products. ................................................................................... 108

Table 3-84: References for power draw by mode estimates for other products.......................................................................... 109

Table 3-85: Annual usage by mode estimates for other products................................................................................................ 110

Table 3-86: References for annual usage by mode estimates for other products........................................................................ 111

Table 3-87: References for installed base estimates for other products. ..................................................................................... 112

Table 4-1: Consumer electronics analyzed in further detail. ........................................................................................................ 115
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List of Acronyms and Abbreviations 

AEC Annual electricity consumption 

AVR Audio-video receivers

CE Consumer electronics 

CEA Consumer Electronics Association 

DOE U.S. Department of Energy 

DTA Digital terminal adapters1

DVD Digital versatile disc 

DVR Digital video recorder

EP Electro-photographic

EPA U.S. Environmental Protection Agency

HD High definition 

IAD Integrated Access Device

LBNL Lawrence Berkeley National Laboratory 

MFD Multi-function device

NA Not applicable

NRD Natural Resources Defense Council

PC Personal Computer

STB Set-top box

TEC Total energy consumption, Typical energy consumption

TV Television 

TWh Terawatt-hour

UEC Unit electricity consumption

USB Universal Serial Bus

VCR Video cassette recorder 

 

1

Also called digital-to-analog converter boxes, digital transport adapters, and digital television adapters. 
Fraunhofer USA Center for Sustainable Energy Systems 10

Acknowledgements

The authors would like to express our gratitude to the following people for their support in making this 

report possible. 

Thanks to the project sponsors at the Consumer Electronics Association, and especially Douglas Johnson, 

Vice President, Technology Policy, for advocating for and leading the project at CEA. In addition, thanks 

to Steve Koenig for providing CE market data and consultations on our installed base estimates and to 

Jessica Boothe and Robin Trembley for their input and collaboration on the CE Usage Survey.

Thanks to our reviewers for reviewing and providing helpful feedback on the draft final report:

 Warren Boxleitner, Nintendo

 Sibylle Braungardt, Fraunhofer Institute for Systems and Innovation Research (ISI) 

 Tim Calland, Microsoft

 Louis-Benoit Desroches, LBNL

 Paul Glist, National Cable and Telecommunications Association (NCTA) 

 Jerry Jessop, Sony 

 Gary Langille, EchoStar

 Lauren Liecau, Unaffiliated 

 Adrian Liga, Apple

 David Maciel, Sony

 R.J. Meyers, EPA ENERGY STAR

 James Morgan, Sony

 Bruce Nordman, LBNL

 Scott O’Connell, Dell

 Verena Radulovic, EPA ENERGY STAR

 Vida Rozite, International Energy Agency

 Mark Sharp, Panasonic

 Hans-Paul Siderius, SenterNovem

 Michael Warnecke, Entertainment Software Association

 Andrew Ware, Logitech

 Liz Westbrook, Trenholm, Natural Resources Canada

 Robert White, Dell

Finally, we would like to thank Paul Semenza with NPD DisplaySearch for providing display data and Ian 

Olgeirson of SNL Kagan for providing set top box data. 
Fraunhofer USA Center for Sustainable Energy Systems 11

Executive Summary

The Consumer Electronics Association (CEA®) commissioned this study to quantify the electricity 

consumption of consumer electronics (CE) in U.S. households in 2013. Relative to other energy end uses, 

the characteristics of CE typically change very quickly due to short product cycles and lifetimes, evolving 

usage patterns and dynamics, and rapid technology adoption that can strongly influence device power 

draw by mode. As a result, the characteristics of the installed base of most CE can change dramatically in 

a few years. Such rapid changes in the energy consumption characteristics of CE make it essential to 

develop up-to-date and accurate assessments of CE energy consumption. If older data are used to 

analyze potential energy policy decisions, such as voluntary or mandatory regulatory programs, they can 

lead to less effective policy decisions that may not achieve their end goals. 

We used a bottom-up approach to characterize U.S. residential consumer electronics (CE) energy 

consumption in 2013. Our effort focused on 17 priority categories, shown in Table ES-1. We selected 

these for more refined AEC analysis based on preliminary AEC estimates (higher more likely to be 

selected) and uncertainty in the preliminary AEC estimate (higher more likely to be selected). In 

addition, we developed preliminary estimates for 29 other CE categories. For each CE category, we used 

a range of sources to develop estimates for the installed base and average power draw and annual 

usage by mode. 

Table ES-1: Consumer electronics analyzed in further detail.

Audio-Visual Equipment Computers & Peripherals

Home Audio

Speaker Dock

Compact Stereo System

Televisions

Video Game Consoles

Set Top Boxes

Cable

Standalone

Satellite

Telco

Desktop PC

Portable PC

Computer Speakers

Computer Monitor

Smart Phone

Tablet 

Networking Equipment

Integrated Access Device 

Modem

Router

Notably, we developed five (5) phone surveys to assess the usage of CE in greater detail, with a 

particular focus on refining our understanding of audio personal computer, smart phone, tablet, 

television, and video game console usage by mode. Subsequently, we used the survey responses as 

inputs into detailed usage-by-mode models.

Overall, we estimate that the 3.8 billion CE in homes consumed 169 TWh in 2013, an amount equal to 

12% of residential electricity consumption and 8.4% of residential primary2energy consumption. Figures

ES-1 and ES-2 show the breakdown in annual electricity consumption (AEC) by category and device. 

 

2

Residential primary energy is the total energy content of the fuel required to meet all end uses. Primary energy includes the fuel consumed at 

the home, as with non-electric space heating applications and appliances (e.g., oil or gas furnaces, gas powered clothes dryers, etc.), as well as 

fuel consumed at the power plant to generate electricity and to overcome transmission and distribution losses. For example, when a home 

consumes 1 kWh of electricity, the power plant must consume an average of 3.1 kWh of primary energy (DOE 2012).
Fraunhofer USA Center for Sustainable Energy Systems 12

Figure ES-1: Residential CE annual electricity consumption by category.

Figure ES-2: Residential CE annual electricity consumption by device.

A limited number of CE categories accounted for the majority of CE electricity consumption. Notably, 

televisions accounted for 30% of residential CE electricity consumption, set-top boxes 18%, and 

computers 13%. The AEC of all the categories analyzed in further detail equals 83% of the estimated 

total residential CE AEC.

The average unit electricity consumption (UEC) of the categories evaluated in detail varies greatly 

among categories, with more than an order of magnitude difference between the categories with the 

highest and lowest UEC, shown in Figure ES-3.

28

1.4

2.6

5.6

12

21

6.7

11

31

50

0 10 20 30 40 50

Other CE Devices

Mobile Computing Devices

Computer Speakers

Computer Monitors

Network Equipment

Personal Computers - All

Home Audio

Video Game Consoles

Set-top Boxs - All

Television

Information

Technology

Home

Entertainment

Annual Energy Consumption [TWh]

28

0.6

0.8

1.9

2.5

2.6

2.7

3.4

3.9

4.8

4.9

5.5

5.7

11

11

15

16

50

0 10 20 30 40 50

Other CE Devices

Tablet

Smart Phone

Speaker Dock

STB - Standalone

Computer Speaker

Modem

STB - Telco

Internet Access Device

Compact Stereo System

Portable PC

Router and other

Computer Monitor

STB - Satellite

Video Game Console

STB - Cable

Desktop PC

Television

Annual Energy Consumption [TWh]
Fraunhofer USA Center for Sustainable Energy Systems 13

Figure ES-3: Annual unit electricity consumption for categories evaluated in detail.

The active mode accounts for 70% of the total AEC of all the categories evaluated in more detail, while 

the idle, sleep, and off modes account for 12, 11, and 7 percent, respectively. This masks large 

differences in the distribution of UEC by mode among different CE categories.

12

4.5

6.1

19

42

45

53

55

58

59

62

75

88

106

112

128

166

186

0 50 100 150 200

Other CE Devices

Smart Phone

Tablet

Speaker Dock

Computer Speaker

STB - Standalone

Portable PC

Modem

Computer Monitor

Router and other

Internet Access Device

Compact Stereo System

Video Game Console

STB - Telco

STB - Satellite

STB - Cable

Television

Desktop PC

Unit Energy Consumption [kWh/year]
Fraunhofer USA Center for Sustainable Energy Systems 14

1 Introduction

The Consumer Electronics Association (CEA) commissioned this study to quantify the electricity 

consumption of consumer electronics (CE) in U.S. households in 2013 as a follow-up to the two prior 

studies it commissioned for 2006 (Roth and McKenney 2007) and 2010 (Urban et al. 2011). Relative to 

other energy end uses, the CE end use characteristics typically change very quickly due to innovation, 

short product cycles and lifetimes, evolving usage patterns and dynamics, and rapid technology 

adoption that can strongly influence device power draw by mode. As a result, the characteristics of the 

installed base of most CE have changed dramatically since the first study.

Such rapid changes in the energy consumption characteristics of CE make it essential to develop up-todate and accurate assessments of CE energy consumption. If older data are used to analyze potential 

energy policy decisions, such as voluntary or mandatory regulatory programs, they can lead to less 

effective policy decisions that may not achieve their end goals. Consequently, CEA commissioned this 

follow-up study to provide high-quality data to inform public policy decisions affecting CE.

1.1 Approach

This study used the same approach as the first two CE energy consumption studies:

1. Develop preliminary Annual Energy Consumption (AEC) estimates for a long list of CE 

2. Select a subset of priority CE for more refined analysis 

3. Develop more refined AEC estimates for the priority categories

4. Compare current energy consumption characteristics with prior estimates

5. Compose a Final Report to CEA suitable for widespread distribution

1.2 Report Organization

The report has the following organization:

Section 2 describes the methodology used to characterize CE energy consumption. 

Section 3 presents an overview of CE energy consumption and the detailed analyses for the priority CE

categories.

Section 4 presents the conclusions of this study.

Appendix A contains the CE Usage Survey.

Appendix B explains our methodology for estimating computer and monitor usage by mode based on 

the CE Usage Survey responses.
Fraunhofer USA Center for Sustainable Energy Systems 15

2 Energy Consumption Calculation Methodology 

We used a bottom-up approach to evaluate the annual electricity consumption (AEC) of each CE 

category shown in Figure 2-1. For each device we developed estimates for the annual average usage in 

each power mode (in hours) and multiplied them by the estimated average power draw in that mode (in 

watts) to calculate the unit electricity consumption (UEC) by mode. The sum of the UEC over all modes 

equals the total device UEC, and the product of the UEC and installed base equals the AEC. The modes 

shown in Figure 2-1 are illustrative and were tailored for the analysis of each specific category.

Figure 2-1: UEC and AEC calculation methodology (ADL 2002).

Prior studies of CE energy consumption describe the methodology in further detail (Kawamoto et al. 

2001, Roth et al. 2002, Roth et al. 2006, etc.). A succinct overview of how we typically evaluated each 

component of the AEC calculation follows.

2.1 Residential Installed Base

The residential installed base equals the total number of devices actively used in homes, excluding 

devices that are not used (e.g., those stored, unplugged in basements or closets). Most installed base 

estimates came from market research studies (most notably CEA 2013 a,b), the CE Usage Survey (see 

Appendix A), and, to a lesser extent, CE sales data. Typically, the installed base estimates have the 

lowest uncertainty of any AEC component. 

2.2 Power Draw by Mode 

All consumer electronics have at least two basic operating modes, e.g., on and off, and most have more. 

For many CE, the operational power draw can vary appreciably due to changes in operation, e.g., 

computer microprocessor utilization scaling, imaging equipment activity, and (in some cases) display 

brightness. For each CE category, we identified the most relevant power modes and developed 

estimates for the average power draw of its installed base in each mode. 

Ideally, our assessment would use measurements of CE deployed in a larger sample (of at least several 

hundred) of demographically representative U.S. households to generate the power draw by mode 

x

Annual Unit

Electricity Consumption

by mode

UECactive

UECsleep

UECoff

Mode

Active

Sleep

Off

Σ

=

=

=

x

x

=

Hours of 

Annual Usage 

by mode

Power

by mode

Pactive

Psleep

Poff

Device Unit

Energy 

Consumption

UEC x IB

Residential 

Installed 

Base

= AEC

Tactive

Tsleep

Toff

Annual Energy

Consumption
Fraunhofer USA Center for Sustainable Energy Systems 16

estimates. Regrettably, the cost and time required to perform such a study lies well beyond the scope of 

this project. Instead, we relied upon several different sources to estimate power draw by mode, 

including: 

 Field measurement campaigns

 CE energy consumption characterization studies

 ENERGY STAR measurement databases

 Targeted measurements by Fraunhofer 

 Measurements by CEA member companies

We were able to consult multiple sources for most CE categories, which increased our confidence in our 

power draw by mode estimates. 

2.3 Annual Usage by Mode

For most CE categories, the annual number of hours that an average device spends in different power

modes is the most difficult aspect of the UEC calculation to accurately estimate. Ideally, the usage 

estimates would be based on a sustained field measurement campaign that accurately recorded the 

time that all CE spent in different modes from a sample of at least several hundred demographically 

representative U.S. households, over the course of weeks or months. Unfortunately, such a thorough 

evaluation is beyond the scope of this study. 

We used instead a combination of approaches to estimate annual usage by mode, including: 

 The CE Usage Survey (see Appendix A)

 Data from prior field measurement campaigns3

 Data from prior CE energy consumption characterization studies

Notably, we used the CE Usage Survey responses as inputs into more refined models to assess computer 

and monitor usage (see Appendix B). We posed more questions for computers and video game consoles

because they have higher AEC values that have particularly high – and are highly sensitive to –

uncertainties in their usage. In addition, we included several questions about smart phone and tablet 

usage because their energy consumption had not been thoroughly characterized in the past. Finally, we 

also fielded surveys about audio products and televisions.

 

3

Although very useful, prior field measurement campaigns usually fall short of the ideal described due to a limited and biased (i.e., non-random 

and unrepresentative) sample of households used and devices measured.
Fraunhofer USA Center for Sustainable Energy Systems 17

3 Energy Consumption of Consumer Electronics in U.S. Homes

3.1 Summary

We estimate that 3.8 billion residential consumer electronics consumed approximately 169 TWh of 

electricity in 2013 (see Table 3-1 and Figure 3-1), an amount equal to 12% of residential electricity 

consumption and 4.5% of total U.S. electricity consumption in 2013 (DOE/EIA 2014a,b). This translates 

into 8.4 and 1.8 percent of residential and U.S. total primary energy consumption4, respectively 

(DOE/EIA 2014a,b). 

Table 3-1: Residential CE energy consumption summary.

Device UEC

[kWh/yr]

Installed Base 

[millions]

AEC

[TWh]

Computers

Desktop 186 88 16

Portable 53 93 4.9

Computer Speakers 42 63 2.6

Computer Monitors 58 97 5.7

Network Devices

Integrated Access Device 62 64 3.9

Modem 55 49 2.7

Router 59 94 5.5

Set-top Boxes 75 67 5.0

Cable 128 113 15

Standalone 45 55 2.5

Satellite 112 94 11

Telco 106 32 3.4

Shelf-Stereo / Compact Audio 75 64 4.8

Smart Phone 4.5 166 0.8

Speaker Dock 19 98 1.9

Tablet Computer 6.1 100 0.6

Television 166 301 50

Video Game Consoles 88 128 11

Other CE Devices 12 2,110 28

Total NA 3,809 169

The remainder of this section presents the analyses for the devices selected for further analysis.

 

4

Using 10,462 Btu of primary energy per kWh of electricity (DOE 2012).
Fraunhofer USA Center for Sustainable Energy Systems 18

Figure 3-1 : UEC, installed base, and AEC of CE categories evaluated in detail.

12

6.1

4.5

19

45

42

55

106

62

75

53

59

58

112

88

128

186

166

0 50 100 150 200

Other CE Devices

Tablet

Smart Phone

Speaker Dock

STB - Standalone

Computer Speaker

Modem

STB - Telco

Internet Access Device

Compact Stereo System

Portable PC

Router and other

Computer Monitor

STB - Satellite

Video Game Console

STB - Cable

Desktop PC

Television

Unit Energy Consumption [kWh/yr]

100

166

98

55

63

49

32

64

64

93

94

97

94

128

113

88

301

0 100 200 300 400

Installed Base [millions]

2,110

28

0.6

0.8

1.9

2.5

2.6

2.7

3.4

3.9

4.8

4.9

5.5

5.7

11

11

15

16

50

0 10 20 30 40 50

Annual Energy Consumption [TWh]
Fraunhofer USA Center for Sustainable Energy Systems 19

3.2 Devices Selected for Further Analysis 

Although this study would have, ideally, evaluated the AEC of all CE in greater detail, time and scope 

constraints required that we focus our effort on a subset of CE where a more refined analysis would 

yield the greatest value. Consequently, in conjunction with CEA, we selected 17 distinct CE categories for 

more refined AEC analysis based on:

 Preliminary AEC estimates (higher more likely to be selected) 

 Uncertainty in the preliminary AEC estimate (higher more likely to be selected). 

Table 3-2 summarizes the categories selected for further analysis. Since a relatively small number of CE 

categories account for the vast majority of all CE energy consumption (see Table 3-1), this approach

does not have a major impact on the accuracy of our estimate for total residential AEC. 

Table 3-2: CE analyzed in the current study.

Analyzed in Higher Detail Analyzed in Lesser Detail

Computer Speaker AV Receiver with surround sound processor

Computer - Desktop Bluetooth Headset

Computer - Portable Blu-ray player

Integrated Access Device Boombox

Modem Camcorder

Computer Monitor Copy machine (stand-alone)

Router Cordless phone

Set-top Box – Cable Digital camera

Set-top Box – Standalone Digital picture frame

Set-top Box – Satellite DVD Player

Set-top Box – Telco eReader

Shelf-Stereo / Compact Audio External Storage Device

Speaker Dock Fax Machine (stand-alone)

Smart Phone Handheld GPS

Tablet Computer Headphones

Television Home Theater in a Box (HTIB)

Video Game Console Internet Phone Device

Mobile (non-smart) Phone

Portable DVD or Blu-ray disc player

Portable Game Devices

Portable media/MP3 Player/CD Player

Portable Wireless Speaker

Printer + MFD (multi-functional device)

Projector

Radio

Scanner (stand-alone)

Soundbar

Telephone Answering Device

Video Cassette Recorder (VCR)
Fraunhofer USA Center for Sustainable Energy Systems 20

3.3 Computer Speakers

3.3.1 Current Energy Consumption

Computer speakers are defined as external, self-powered systems that reproduce audio signals 

generated by a computer. They typically incorporate a built-in amplifier powered by a dedicated internal 

or external power supply that draws less power than home theater and stereo systems. Some smaller 

systems, especially for portable computers, are powered directly through a USB port. This analysis 

excludes those devices, as in the previous report (FhCSE 2011). A typical computer speaker system 

configuration includes either two speakers without a subwoofer, or two or five speakers with a 

subwoofer (2.1 system/5.1 channel surround system). We were unable to find precise data on the 

breakdown of speaker systems by the number of channels they have; however, we were able to 

breakdown the installed base between speakers with and without a subwoofer in this study. 

3.3.1.1 Installed Base

The 2013 CE Usage Survey included questions about two types of computer speaker systems in 

households, namely, computer speakers with and without a subwoofer. Figure 3-2 summarizes the 

results for the portion of desktop and portable computers with zero, one, two, three or four and more 

computer speaker systems with and without subwoofer connected. The CE Usage Survey found that 

40% of primary computers (i.e., the most-used computer in a household) were connected to at least one 

computer speaker system without a subwoofer and 19% of primary computers were connected to a 

computer speaker system with a subwoofer. On average, secondary desktop computers had slightly 

fewer computer speaker systems without and with a subwoofer, 29% and 16%, respectively. We did not 

ask about speakers connected to a third computer. Instead, we assumed that the proportion of the 

remaining computers with a speaker system has not changed from 2010, i.e., we estimated that 16% of 

tertiary desktop computers had an external speaker (FhCSE 2011). In contrast, the survey responses 

indicated that less than 10% of primary and secondary portable computers were connected to any kind 

of computer speaker system. In total, we estimate that 72% of all residential computers are not 

connected to a computer speaker system.

Figure 3-2: Distribution of computer speaker systems per desktop and portable computer.

The CE Usage Survey data for computers found an installed base of the 88 million home desktop 

computers and 93 million home portable computers, of which 60% and 57% are used as the primary 

11%

55%

29%

5%

0% 0%

11%

71%

15%

2% 1% 0%

0%

20%

40%

60%

80%

100%

Don’t know 0 1 2 3 4+

Desktop Computer

Speakers without a subwoofer

Speakers with a subwoofer

6%

87%

6%

1% 0% 0%

6%

89%

4% 0% 0% 0%

0%

20%

40%

60%

80%

100%

Don’t know 0 1 2 3 4+

Portable Computer

Speakers without a subwoofer

Speakers with a subwoofer
Fraunhofer USA Center for Sustainable Energy Systems 21

desktop computer and primary portable computer, respectively. This yields an installed base of 63 

million computer speaker systems (Table 3-3), and represents a 15 percent decrease in the installed 

base of computer speaker systems from 2010 (FhCSE 2011). This likely is due to the recent decrease in 

the installed base of desktop PCS (13% since 2010), since the survey indicates that most computer 

speakers are used with desktop PCs. 

Table 3-3: Installed base of computer speaker systems (CE Usage Survey).

Type Home Computers

[millions]

% with speakers and 

no subwoofer

% with speakers and 

a subwoofer

Total

[millions]

Desktop 88 39% 20% 52

Portable 93 7% 5% 11

Total/Avg. 181 23% 12% 63

The data indicate a household penetration rate of 35% for computer speaker systems without a 

subwoofer and 18% for speaker system with a subwoofer. We could not find other estimates for the 

installed base of computer speaker systems.

3.3.1.2 Unit Energy Consumption

3.3.1.2.1 Power Draw

Computer speaker systems can be characterized by three operating modes (FhCSE 2011):

 Active – Device is actively used, playing music or other audio 

 Active standby – Device is neither playing audio, nor turned off manually

 Off – Device is turned off manually but remains connected to the energy source.

Since we could not find new data sources for computer speaker power draw by mode, we measured the 

power draw in Jan. 2014 of two computer speaker systems with a subwoofer (2.1 channel) and one 

computer system without a subwoofer (2.0). Specifically, we selected computer speaker systems to 

measure from the best-selling units sold at Amazon.com and Best Buy. The one 2.0 computer speaker 

system had a maximum power draw of 4 W at maximum volume, whereas in 2010 a 2.0 computer 

speaker system drew an average 6 W in active mode (Meister et al. 2011).

Due to the limited number of measurements, we used straight averages to calculate the power draw for 

computer speakers in different modes. The straight average power draws for computer speakers 

without a subwoofer, we estimated from 18 speakers5 measured by ECOS (Meister et al. 2011), 6 

speakers measured by ECW (Bensch et al. 2010), and the one 2.0 speaker system we measured in 2014. 

In contrast, a very small sample (n=4) of 2.1 system power draw measurements from Meister et al. 

(2011) and Fraunhofer6has an average power draw of 44W. Results are shown in Table 3-4.

 

5 Meister et al. (2011) notes n=18 in the Appendix and n=20 in its Figure 17.

6

Two 2.1 computer speaker systems were measured and had an average active-mode power draw of 15W.
Fraunhofer USA Center for Sustainable Energy Systems 22

Table 3-4: Power draw by mode for computer speaker systems.

Type

Power [W] Sources Active Active Standby Off

Without Subwoofer 5.5 2.4 1.6 Fraunhofer measurements, Meister et al. 2011, Bensch et al. 2010 

With Subwoofer 44 7.5 1.2 Fraunhofer measurements, Meister et al. 2011

3.3.1.2.2 Usage

We did not ask about computer speaker usage in the 2013 CE Usage Survey, so we based our usage 

estimates on the findings from the 2010 CE Usage Survey (FhCSE 2011). Thus, we assumed that usage 

patterns have not changed appreciably since 2010. We did, however, scale the 2010 usage estimates 

with computer usage in 2013. In the 2010 CE Usage Survey, 61% of U.S. adults answered that their 

computer speakers are always on when the computer is used, i.e. 3.1 hours per day on average, another 

30% are on often or half of the time the computer is used, which results in an active use of 2.7 hours per 

day. The data suggest in 2010 that 61% of computer speaker systems are not switched off over night. 

During the day when the computer is not in use, 39% of computer speakers are never off, while 54% are 

reported to be always or often off and 17% are reported off occasionally or half of the time. Overall, this 

suggests that the average speaker system spends 11% of the day in active mode, 47% of the time in 

active standby mode, and 42% of time in off mode (Table 3-5).

Table 3-5: Annual usage by mode of computer speaker systems (hours/year).

Active Active standby Off Sources

986 4,125 3,649 Current study computer usage, FhCSE 2011

Versions 2.0 and 3.0 of the ENERGY STAR specifications for audio products both require qualifying 

devices to have auto power down (APD) functionality with a default setting of two hours or less. This 

would tend to decrease the time spent in active standby mode by ENERGY STAR devices (EPA 2013). As 

of May, 2014, the ENERGY STAR products database did not include any computer speakers; therefore

we did not include APD in our computer speaker usage model. 

3.3.1.2.3 Unit Energy Consumption 

We calculate a computer speaker UEC of 42 kWh/year (see Table 3-6).

3.3.1.3 Annual Energy Consumption

We estimate that computer speakers consumed 2.6 TWh in 2013. Systems with a subwoofer accounted 

for about 65% of the AEC (see Figure 3-3 and Table 3-6). 

Figure 3-3: Unit Energy Consumption by mode and Annual Energy Consumption by computer speaker system type.

Active Active 

standby Off

0 15 30 45

UEC [kWh/year]

With 

subwoofer

Without 

subwoofer

0 1 2 3

AEC [TWh]
Fraunhofer USA Center for Sustainable Energy Systems 23

Table 3-6: UEC and AEC calculation for computer speaker systems.

Type

Installed

[millions] Percent

Power [W] UEC [kWh/yr] AEC

Active Standby Off Active Standby Off Total [TWh]

Without Subwoofer 42 65% 5.5 2.4 1.6 5.4 10 6.0 21 0.9

With Subwoofer 21 35% 44 7.5 1.2 44 31 4.5 79 1.7

Total/Wt. Avg. 63 100% 19 4.0 1.5 19 17 5.5 42 2.6

3.3.2 Comparison with Prior Energy Consumption Estimates

We estimate that the UEC value has increased from 2010 due to the integration of higher power 

speakers systems with subwoofers into our energy model. On the other hand, total AEC decreased 7% 

from 2010, reflecting a 15% decrease in the installed base of computer speakers systems (Table 3-7). 

Table 3-7: Prior energy consumption estimates for computer speaker systems.

Year Installed Power [W] Usage [h/yr] UEC AEC Source [millions] Active Standby Off Active Standby Off [kWh/yr] [TWh]

2013 63 19 4 1.5 986 4,125 3,649 42 2.6 Current

2010 74 8 4 3 1,314 4,380 3,066 37 2.8 FhCSE 2011

3.3.3 References 

ECW. Bensch, I., S. Pigg, K. Koski and R. Belshe. 2010. “Electricity Savings Opportunities for Home 

Electronics and Other Plug-In Devices in Minnesota Homes – A technical and behavioral field 

assessment.” Final Report by the Energy Center of Wisconsin, Report 257-1. May. 

EPA. 2013. ENERGY STAR program requirements Audio/Video. Version 3.0. U.S. Environmental 

Protection Agency. http://www.energystar.gov/ia/partners/prod_development/ 

revisions/downloads/audio_video/Final_Version_3_AV_Program_Requirements.pdf?5c24-7fe5. May.

FhCSE. Urban, Bryan, Kurt Roth, and Verena Tiefenbeck. 2011. “Energy Consumption of Consumer 

Electronics in U.S. Homes in 2010.” Final Report to the Consumer Electronics Association. 

http://www.ce.org/CorporateSite/media/Government-Media/Green/Energy-Consumption-of-CE-inU-S-Homes-in-2010.pdf. Dec.

Meister, B.C., C. Scruton,V. Lew, L. ten Hope and M. Jones. 2011. “Office Plug Load Field Monitoring 

Report.” Final Field Project Report by Ecos Consulting to the California Energy Commission. 

http://www.energy.ca.gov/2011publications/CEC-500-2011-010/CEC-500-2011-010.pdf. Apr.
Fraunhofer USA Center for Sustainable Energy Systems 24

3.4 Desktop Computers

Desktop computers include personal computers (PCs) housed in a box and computers with built-in 

monitors called All-in-One (AIO) PCs (also known as integrated desktop computers), such as iMac.

3.4.1 Current Energy Consumption

3.4.1.1 Installed Base

We estimate an installed base of 88 million desktop PCs that have been used in the past month. This 

equals 83% of the ownership installed base of 105-113 million estimated reported by CEA (2013a,b). As 

with our 79% plugged-in rate in 2010 (FhCSE 2011), this difference likely reflects that some desktop PCs 

in homes have not been recently used. Indeed, our estimate of ownership penetration for desktop PCs 

of 62% agrees with other sources (see Table 3-8). 

Although our plugged-in penetration estimate of 44% is lower than our previous report (62%, 

Fraunhofer 2011), we think it is more accurate, because the 2013 CE Usage Survey includes questions 

that more precisely distinguish between device ownership and plugged-in status during the past month. 

Therefore, these results provide a richer representation of the plugged-in and ownership installed bases.

Table 3-8 : Installed base estimates for desktop PCs from different data sources.

Year Description Household 

penetration

Households

[millions]

Units/owner

household

Installed Base 

[millions] Source

2013

2013

Desktop PCs plugged in last month 44% 53 1.67 88 CE Usage Survey

Desktop PC ownership 62%*74 - - CE Usage Survey

2013 Desktop PC ownership 63% 75 1.41 105 CEA 2013a

2013 Desktop PC ownership - - - 113 CEA 2013c

2013 Desktop PC ownership - - - 114 DRG 2013

2011 Desktop or portable PC ownership 76%†- - - U.S. Census 2013

2012 Desktop or portable PC ownership - - 1.80‡- A&E 2012

2013 Desktop PCs plugged in - - - 88 Representative

* Estimated based on survey responses that indicated no ownership of desktop PCs (0 desktop PCs plugged in, but ≥1 owned, see Figure 3-4).

To understand PC usage, we asked about the most used (primary) and second-most used (secondary) 

desktop PCs. We classified desktop PCs without an external monitor as an AIO unit. In addition, we 

assumed that AIO desktop PCs will tend to be the primary or secondary desktops given their recent 

introduction into the market.

Table 3-9: Plugged-In installed base estimates for Tower and All-in-One (AIO) Desktop Computers from CE Usage Survey.

Type

Households [millions]

Plugged-In [million units]

Not Owned

PCs Plugged-In per Owner Household 

0 1 2 3 ≥4 ≥1†All Primary Second+

Tower 45 21 26 4.1 1.8 3.4 35 69.6 37 34

All-in-One - - 16 1.0 - - 17 18.0 16 1.0

Any Desktop 45 21 42 5.1 1.8 3.4 53 87.6 53 35

† Equivalent to the household penetration of plugged-in PCs.

Primary: number of primary PCs.

Second+: number of PCs that are not primary, i.e., secondary, tertiary, etc.; treated as secondary in energy model.
Fraunhofer USA Center for Sustainable Energy Systems 25

Figure 3-4: Distribution of households with numbers of desktop PCs plugged in during the past month (Nov 2013).

We compared the AIO installed base estimates with sales data from DisplaySearch (2011-2013). Given 

an average age of desktop PCs of 3.2 years (CEA 2014), we consider a retirement age of 4 years for AIO 

desktop PCs along with sales of AIO PCs since 2009 to develop another estimate of the installed base of 

AIO desktop PCs of 16.3 million. This assumes that no units sold since 2009 have been retired (see Table 

3-10). This generally agrees with the 18 million units from the 2013 CE Usage Survey.

Table 3-10: Plugged-In installed base estimate for All-in-One Desktop Computers based on sales via consumer channels 

(DisplaySearch 2014).

2009e2010 2011 2012 2013 Q1-Q3

Sales (All North America) - 3.6 3.2 3.1 3.7

Sales (U.S. Only)†- 3.2 2.9 2.8 3.3

Installed Base since year (U.S.) 16.3 12.2 9.0 6.1 3.3

† Adjusted based on U.S. and Canada population ratios, 316M and 35M (U.S. Census 2013, Statistics Canada 2013).

e

Estimated based on extrapolation from 2010-2013. 

3.4.1.2 Unit Energy Consumption 

3.4.1.2.1 Power Draw

PC power draw varies with operational mode. For our analysis, we use the modes defined in the ENERGY 

STAR requirements for Computer v6.0 (EPA 2013a):

 Active: When the PC is actively used, or idles for a short while awaiting user input and before 

entering lower power modes.

 Short Idle: When the PC has been idle for about 5 minutes and has entered a low power mode 

with the monitor still on.

 Long Idle: When the PC has been idle for about 15 minutes and has entered a low power mode 

with the monitor off.

 Sleep: Entered manually or automatically after about 30 minutes from which the PC can quickly 

wake. 

 Off: PC is turned off but remains plugged in.

The main difference from the previous ENERGY STAR specification (v5.2) is the splitting of the idle state 

into Short and Long Idle to better characterize computers with integrated monitors (i.e., AIO desktop

PCs).

0%

10%

20%

30%

40%

0 1 2 3 ≥4

Weighted % of

U.S. Households

Tower

AIO
Fraunhofer USA Center for Sustainable Energy Systems 26

Table 3-11 presents recent power draw estimates for desktop PCs. Together, these sources indicated 

that average power draw values have decreased for all modes since 2010. The much larger difference 

between short idle and long idle mode power draw of the AIOs relative to the Towers reflects the power 

draw of the integrated display.

Table 3-11: Power draw estimates for desktop computers from different data sources.

Type Power Draw [W] Year Source Active Short Idle Long Idle*

Sleep Off

Tower - 48 47 2.5 1.1 2012 EPA 2013b†

Tower - - 46 2.1 1.0 2013 NRDC 2013

AIO - 63 36 1.9 0.9 2012 EPA 2013b†

AIO - - 30 1.8 0.9 2013 NRDC 2013

Any Desktop - 51 45 2.4 1.0 2012 EPA 2013b†

Any Desktop - 67 - 2.4 0 2012 LBNL 2013‡

Any Desktop - - 60 4 2 2010 Fraunhofer 2011

* The ENERGY STAR v6.0 specification for computers maps the Idle mode of v5.2 as equivalent to Long Idle in v6.0.

† Power draw of each test device in the dataset reweighted based on the portion of unit sales (21%) meeting the ENERGY STAR v6.0 

specifications (EPA 2012).

‡ The field study (with 39 desktop PCs) had grouped modes as “high power”>10W, “low power”≤10W, and "off"=0W. This roughly maps 

to Short Idle and Sleep power draws, respectively, in the ENERGY STAR v6.0 specification for computers.

We use data from these data sets to derive a representative estimate of power draw for different modes 

(see Table 3-11). In particular, we consider a mixture of newer and older PCs in the total installed base. 

We use power draw values from the ENERGY STAR v6.0 dataset of qualified and unqualified PCs (EPA 

2013b) to represent PCs sold from 2011 to 2013, and power draw values from our previous study 

(Fraunhofer 2011) to represent older PCs. We use the results of (CEA 2014) for the age of desktop PCs 

owned to derive a relative weight between newer and older PCs (Table 3-12).

Table 3-12: Estimated desktop PC installed base by computer vintage to evaluate relative power draw characteristics derived 

from Figure 3 of (CEA 2014). Average age: 3.2 years.

“Older” “Newer”

Year of Purchase 2009 2010 2011 2012 2013

Age ≥4 3 2 1 <1

% of Desktop PCs Owned 10% 12% 19% 18% 41%

41% 59%

Source for Power Draw Model Fraunhofer 2011 EPA 2013b

Most of the data sources in Table 3-11 do not include estimates for power draw in active mode. Based 

on metered power draw of one notebook in a commercial setting, NRDC estimates an active power 

draw overhead of 30% more than in idle mode (NRDC 2013). This overhead is similar to that reported by 

CEC (2012), which metered one desktop PC purchased in 2007 running an office productivity benchmark 

test. A lab metering study of four desktop PCs browsing consumer-oriented websites and videos found 

lower overhead of 8-21% (Fraunhofer 2013). Therefore, we apply a scaling factor of 115%, i.e., active 

mode power draw is 15% higher than short idle mode power draw. Ultimately, the power draw values 

by mode that we use to represent the installed base agree quite well with the LBNL field monitoring 

study of 559 households (LBNL 2013).
Fraunhofer USA Center for Sustainable Energy Systems 27

Figure 3-5: Representative power draw by mode of tower and AIO desktop PCs.

3.4.1.2.2 Usage

A desktop PC enters different operational modes depending on whether the user is currently using it, 

how recently it was last used, how the user manually manages its power, and its automatic power 

management settings. We compute the time each PC spends in different operational modes using the 

energy model presented in Appendix B.1. Our model draws heavily on the data gathered from the CE 

Usage Survey, where we asked respondents about their household use of the two most used desktop 

PCs. The subsequent subsections explain findings for key aspects of the model in more detail.

3.4.1.2.2.1 Usage per Session

We evaluated the active usage of PCs during the day for each session and for the whole day to account 

for the cumulative time desktop PCs spend in different operational modes. More specifically, we 

evaluated the usage for different periods of the day, pre-evening (morning and afternoon) and evening,

via specific survey questions, and inferred usage for weekdays or weekends based on what day 

“yesterday” was for the survey response. On average, households’ primary desktop PCs are used about 

two times before the evening, and about once in the evening. In contrast, secondary PCs are used about 

half as frequently. For both primary and secondary desktop PCs, we found that each session lasts for 

about one hour, and appears to be shorter on weekend days than on weekdays (Figure 3-6).

65

87

70

57

75

61

56

42

54

3.5 2.7 3.4 1.6 1.4 1.6

0

20

40

60

80

100

Tower All-in-One Any Desktop

Power Draw [W] Active Short Idle Long Idle Sleep Off
Fraunhofer USA Center for Sustainable Energy Systems 28

Primary Desktop PC

Secondary Desktop PC

Figure 3-6: Average per session usage duration and number of sessions “yesterday” for primary and secondary desktop PCs.

3.4.1.2.2.2 Usage per Day

On average, households use primary and secondary desktop PCs for about 3 to 4 hours per day, with the 

primary desktop PC used somewhat more than secondary ones (3.9 vs. 3.0 hours).

Primary Secondary

Figure 3-7: Total usage duration “yesterday” for primary and secondary desktop PCs.

3.4.1.2.2.3 Power Management

PC energy consumption can be reduced through power management (PM). The user may do so using 

manual routines of power management (e.g., by putting the PC to sleep at night), or by enabling 

automatic PM settings (e.g., auto-hibernate to have the computer save its state and automatically turn 

off after a chosen period of inactivity). We discuss these two manual and automatic power management 

methods in the next section.

1.2 1.3

1.1 1.1 1.2

0.8

0

1

2

Any Day Week-day Week-end

Per Session Usage [hours]

Pre-Evening Evening

1.7 1.6

2.0

1.2 1.3

1.0

0

1

2

Any Day Week-day Week-end

# Sessions per Day

Pre-Evening Evening

1.0

1.1

0.6

1.3

1.4

0.8

0

1

2

Any Day Week-day Week-end

Per Session Usage [hours]

0.8 0.7

1.0

0.8 0.9

0.6

0

1

2

Any Day Week-day Week-end

# Sessions per Day

0

1

2

3

4

5

Any Day Weekday

Weekend

Evening 1.6 1.8 1.1

Pre-Evening 2.3 2.4 2.1

Whole Day 3.9 4.1 3.2

h/day

0

1

2

3

4

5

Any Day Weekday

Weekend

Evening 1.7 1.9 1.0

Pre-Evening 1.4 1.3 1.5

Whole Day 3.0 3.2 2.6

h/day
Fraunhofer USA Center for Sustainable Energy Systems 29

Manual Power Management

We asked U.S. adults how often they manually turned their PC off or put it to sleep. The survey results 

indicate that users tend to manually turn off their desktop PCs (40% of the time during the day and 56% 

at night), while leaving them on 37% of the time during the day. Desktop PCs are manually put to sleep 

about 22% of the time during the day. However, even if a PC is left on, automated PM may cause the PC 

down to a low power mode.

Daytime Night*

* Night-sleep and -left-on determined from daytime ratios.

Figure 3-8: Likelihood of users manually setting desktop PCs into various modes for the daytime or night.

Automatic Power Management Setting

To infer the automatic PM settings, we asked U.S. adults about the initial state or start-up duration of

their PC at the start of the day “yesterday” if they were the first to use it. For example, if the display is 

already on, this indicates that PM is disabled, while if the computer takes more than a few seconds to 

boot up, auto-hibernate is enabled. We also account for whether the U.S. adult shad manually turned 

the PC off. Our model assumes that PCs with auto-hibernate enabled also have auto-sleep enabled, and 

PCs with auto-sleep enabled have auto-screen off enabled. Based on the survey responses, 90% of 

desktop PCs have some level of power management enabled, particularly with auto-screen off (53%) 

where the PC enters short idle mode, followed by auto-sleep (31%), which engages the long idle mode.

Figure 3-9: Percentage of desktop PCs with different automatic PM modes enabled. 

3.4.1.2.2.4 Time in Operational Modes

Though not necessarily the same, the time distributions for different desktop types (Tower vs. AIO) and 

priorities (primary vs. secondary) are very similar. We present only their weighted average, but account 

for the differences in the energy model analysis. 

32%

45% 37%

25%

18%

22%

43% 37% 40%

0%

20%

40%

60%

80%

100%

Primary Secondary Any Desktop

% of Users with Manual 

Power Management

Off

Sleep

Left On

23%

34% 27%

18%

14%

16%

59% 53% 56%

0%

20%

40%

60%

80%

100%

Primary Secondary Any Desktop

10% 6% 7%

30% 32% 31%

51% 49% 53%

9% 14% 10%

0%

20%

40%

60%

80%

100%

Primary Secondary† Any Desktop

% Desktop PCs in Power 

Management Mode

PM Disabled

Auto-Screen Off

Auto-Sleep

Auto-Hibernate

†High uncertainty for secondary PC,

37% of responses are “Don’t Know.”
Fraunhofer USA Center for Sustainable Energy Systems 30

Figure 3-10 shows the average amount of time each desktop PC spent in various operational modes. 

Desktop PCs spend a considerable amount of time in sleep and off modes (68%) mainly due to manual 

power management or automatic powering down after each session of use. Table 3-13 shows our 

results for the portion of time in Active + Idle modes; they are similar to those from other studies.

‡ Our model defines night as when the household has gone to sleep, so we assume no active usage.

Figure 3-10: Average time spent in various operational modes in one day and in one year for desktop PCs. Weighted average 

across primary and secondary tower and AIO desktop PCs.

Table 3-13: Comparison of percentage of time desktop PCs spent in various operational modes with other data sources.

Time [%] in Operational Mode

Active Short Idle Long Idle Active + Idle Sleep Off Year Setting Source

14% 5.2% 12% 32% 24% 44% 2013 Residential CE Usage Survey

- 32% - 32% 48% 20% 2012 Residential LBNL 2013*

18% - 21% 39% 25% 36% 2010 Residential Fraunhofer 2011

- 35% 15% 50% 5% 45% 2013 Office ENERGY STAR v6.0 (EPA 2013a)†

- - 40% 40% 5% 55% 2009 Office ENERGY STAR v5.2 (EPA 2009)†

41% - - 41% 48% 20% 2008 Office Microsoft 2008

* Field measurement with a small sample size of 39 desktop PCs.

† ENERGY STAR values are based on studies of computer usage in office buildings (ECMA 2010, Microsoft 2009).

3.4.1.3 Unit and Annual Energy Consumption 

We compute the energy consumption by multiplying the time a PC spends in each operational mode

with the corresponding power draw in that mode. Figure 3-11 shows the energy consumption in various 

operational modes. Active usage accounts for the largest portion of energy consumption (47%), 

followed by long idle (31%), then short idle (15%). Together, sleep and off modes combine for 7% of 

energy consumption.

0

4

8

12

16

20

24

Whole

Day

PreEvening Evening Night‡

Off 11 3.8 2.1 4.7

Sleep 5.7 2.6 1.4 1.8

LongIdle 3.0 1.2 0.7 1.1

ShortIdle 1.3 0.6 0.4 0.3

Active 3.4 1.9 1.6 0.0

Total 24 10 6.1 7.9

hours/day

0

2,000

4,000

6,000

8,000

All Days Weekdays

Weekends

Off 3,883 2,570 1,339

Sleep 2,088 1,484 604

LongIdle 1,083 902 161

ShortIdle 458 357 99

Active 1,248 944 300

Total Plugged In 8,760 6,257 2,503

hours/yr
Fraunhofer USA Center for Sustainable Energy Systems 31

‡ Our model defines night as when the household has gone to sleep, so we assume no active usage.

Figure 3-11: Total energy consumed in various operational modes in one day and in one year for desktop PCs. Weighted 

average across primary and secondary tower and AIO desktop PCs.

We found that the Unit Energy Consumption (UEC) of a typical desktop PC is 186 kWh/year, with tower 

and AIO desktop PCs having similar UECs. The Annual Energy Consumption (AEC) for all desktop PCs is 16 

TWh/year.

Table 3-14: UEC and AEC values for desktop PCs.

Type Energy Consumption

[Wh/day]

UEC [kWh/yr] Installed Base

[millions]

AEC

Active Short Idle Long Idle Sleep Off Total [TWh/yr]

Tower 514 87 24 63 7.3 6.2 188 70 13

AIO 505 89 43 41 5.6 5.7 184 18 3.3

Any Desktop 511 87 28 58 7.0 6.2 186 88 16

3.4.2 Comparison with Prior Energy Consumption Estimates

We found a decrease in the both desktop PC UEC and AEC from 2010. A major reason is the drop in 

plugged-in installed base (101 to 88 million) driven by a sharp decrease in sales market share (22% in 

2010 to estimated 8% in 2013, CEA 2013b) and resulting decreased household ownership installed base 

of desktop PCs (128 million (CEA 2010) to 105 million (CEA 2013a)) and almost a 10-fold increase in the 

ownership of tablets, from 4% (Fraunhofer 2011) to 39% (CEA 2013a). This trend could also explain the 

decrease in active use time which we found. 

We refined our computer usage survey from 2010, and believe that it increases the accuracy of our 

estimates for time in operational modes for desktop PCs. Specifically, we have increased the precision of 

our survey questions by asking about three times of day (morning, afternoon, and evening) that are in 

better agreement with our analysis of usage patterns reported in ATUS (2012); see details in Appendix 

Section B.1.3. This provides a richer representation of usage throughout the whole day than our 

previous estimates (Fraunhofer 2011). In addition, breaking the day into more discrete time periods 

should increase the accuracy of peoples’ responses for total computer usage.

On the other hand, our estimate for the portion of PCs with PM enabled is lower than our previous 

report (38% vs. 70%) due to several improvements in our energy model. First, we infer PM settings by 

0

100

200

300

400

500

600

Whole

Day

PreEvening Evening Night‡

Off 17 6.2 3.4 7.6

Sleep 19 8.6 4.6 5.9

LongIdle 160 64 36 61

ShortIdle 76 35 23 18

Active 238 129 109 0

Total 511 243 175 92

Wh/day

0

50

100

150

200

All Days Week-days Weekends

Off 6.2 4.1 2.2

Sleep 7.0 5.0 2.0

Long Idle 58 49 9

Short Idle 28 22 6.0

Active 87 66 21

ALL 186 145 40

kWh/yr
Fraunhofer USA Center for Sustainable Energy Systems 32

asking about the PC state at the beginning of the day (vs. anytime during the day) and this better 

captures the PM settings by eliminating usage by other household members of which the respondent 

may be unaware. Next, to estimate the portion of PCs in auto-hibernate, we subtract responses that 

indicated that the PC was manually turned off at night from responses that indicated the PC is off at the 

beginning of the day. Therefore, assuming that users who manually turn off their PCs do not use autohibernate, this significantly reduces the portion of PCs with auto-hibernate enabled.

Table 3-15: Current and prior energy consumption estimates for desktop PCs.

Year Units

[millions]

Power Draw [W] Time in Mode [hr/yr] PM*

Enabled

UEC

[kWh/yr]

AEC

[TWh/yr] Source Active Sleep Off Active Sleep Off

2013 88 62†3.4 1.6 2,789‡2,088 3,883 38% 186 16 Current

2010 101 60 4 2 3,420 2,150 3,190 70% 220 22 Fraunhofer 2011

2006 90 75 4 2 2,954 350 5,456 20% 235 21 TIAX 2008

2005 85 75 4 2 2,950 350 5,460 20% 234 20 TIAX 2006

2005 108 58 - 3 2,116 - 183 15% 151 16 CCAP 2005

2001 68 50 25 1.5 1,495 163 7,102 20% 90 6.1 LBNL 2004

1999 54.5 50 25 2 717 65 7,978 25% 49 2.7 LBNL 2001

* Percent of computers with power management enabled, i.e., auto-sleep or auto-hibernate, but excluding auto-screen off.

† Weighed average of power draw for active, short idle, and long idle modes.

‡ Combined time in active, short idle, and long idle modes.

3.4.3 References

A&E. 2013. “The Infinite Dial 2013: Navigating Digital Platforms.” Arbitron & Edison Research. Apr. 2, 

2013. http://www.arbitron.com/downloads/InfiniteDial2013.pdf. Retrieved Sept. 16, 2013.

A&E. 2012. “The Infinite Dial 2012: Navigating Digital Platforms – Presentation Companion.” Arbitron & 

Edison Research. April, 2012. http://www.edisonresearch.com/wpcontent/uploads/2012/04/2012_infinite_dial_companion_report.pdf. Retrieved Sept. 16, 2013.

ATUS. 2012. “American Time Use Survey — 2012 Microdata Files.” Jun. 20, 2013. United States 

Department of Labor. http://www.bls.gov/tus/datafiles_2012.htm. Retrieved Oct. 30, 2013.

CEA. 2010. “12th Annual household CE Ownership and Market Potential.” CEA Market Research Report. 

Consumer Electronics Association. May, 2010. Consumer Electronics Association.

CEA. 2013a. “15th Annual CE Ownership and Market Potential Study.” CEA Market Research Report, 

April, 2013. Consumer Electronics Association.

CEA. 2013b. “U.S. Consumer Electronics Sales & Forecasts 2009-2014.” CEA Market Research Report, 

July, 2013. Consumer Electronics Association.

CEA. 2013c. Steve Koenig. Private correspondence, Nov. 2013. Consumer Electronics Association.

CEA. 2014. “Consumer Outlook on Tablets – Jan. 2014 Edition.” Jan.

CEC. 2012. “How low can you go? A White Paper on Cutting Edge Efficiency in Commercial Desktop 

Computers.” Public Interest Energy Research (PIER) Program Final Project Report. Ecos Consulting. 

Mar. 2012. http://www.energy.ca.gov/2012publications/CEC-500-2012-065/CEC-500-2012-065.pdf. 

Retrieved Feb. 3, 2014.

DisplaySearch. 2014. “DisplaySearch Quarterly Desktop Monitor Shipment and Forecast Report, 2011-

13.” Jan. 2014.

ECMA. 2010. ECMA-383 3rd Edition - Majority Profile. Dec. 2010. http://www.ecmainternational.org/publications/files/ECMA-ST/ECMA-383.pdf. Retrieved Dec. 9, 2013.
Fraunhofer USA Center for Sustainable Energy Systems 33

EPA. 2009. “ENERGY STAR Computer Program Requirements Version 5.2.” 

https://www.energystar.gov/ia/partners/product_specs/program_reqs/Computers_Program_Requir

ements.pdf?0e9f-5a79. Retrieved Jan. 30, 2014.

EPA. 2012. “ENERGY STAR Unit Shipment and Market Penetration Report 2012.” December, 2012. 

http://www.energystar.gov/ia/partners/downloads/unit_shipment_data/2012_USD_Summary_Repo

rt.pdf. Retrieved Sept. 16, 2013.

EPA. 2013a. “ENERGY STAR Computer Program Requirements Version 6.0.” Sept. 12, 2013. 

http://www.energystar.gov/products/specs/computer_specification_version_6_0_pd. Retrieved Dec. 

12, 2013.

EPA. 2013b. “ENERGY STAR Computers Draft 2 Version 6.0 Dataset.” May 15, 2012. 

https://www.energystar.gov/products/specs/system/files/Computers_Draft_2_Dataset_masked.xlsx. 

Retrieved Sept. 16, 2013.

EPA 2013c. “ENERGY STAR Qualified Product List.” Oct. 28, 2013. 

http://downloads.energystar.gov/bi/qplist/Computers_Product_List.xls. Retrieved Feb. 5, 2014.

FhCSE. Urban, Bryan, Kurt Roth, and Verena Tiefenbeck. 2011. “Energy Consumption of Consumer 

Electronics in U.S. Homes in 2010.” Final Report to the Consumer Electronics Association. 

http://www.ce.org/CorporateSite/media/Government-Media/Green/Energy-Consumption-of-CE-inU-S-Homes-in-2010.pdf. Dec.

FhCSE. 2013. Roth, K., S. Patel, and J. Perkinson. “The Impact of Internet Browsers on Computer Energy 

Consumption.” Jun. 2013.

LBNL. 2013. Greenblatt, J. B. 2013. “Field data collection of miscellaneous electrical loads in Northern 

California: Initial results.” Lawrence Berkeley National Laboratory. LBNL Paper LBNL-6115E. Jul. 22, 

2013. http://escholarship.org/uc/item/5cq425kt. Retrieved Sept. 16, 2013.

Microsoft. 2008. “Microsoft Power Transition Report.” Microsoft Corporation. 

http://www.energystar.gov/ia/partners/prod_development/revisions/downloads/computer/Microso

ft_PowerTransitionReport.pdf?%20f0fe-40d2. Retrieved Dec. 9, 2013.

Pew. 2012. “Adult gadget ownership over time.” Pew Internet surveys 2006-2013. April, 2012. 

http://www.pewinternet.org/Trend-Data-(Adults)/Device-Ownership.aspx. Retrieved Oct. 30, 2013.

Pew. 2013. “Demographics of internet users” Apr. 17 – May 19, 2013. http://pewinternet.org/StaticPages/Trend-Data-(Adults)/Whos-Online.aspx. Retrieved Jan. 30, 2014.

NRDC. 2013. “NRDC’s Response to CEC’s Invitation to Participate in the Development of Appliance 

Energy Efficiency Measures. NRDC Computers Attachment 2. ENERGY STAR v6.0 Dataset v2 with 

additions from NRDC.” May 9, 2013. 

http://www.energy.ca.gov/appliances/2013rulemaking/documents/responses/Consumer_Electronic

s_12-AAER2A/NRDC_Response_to_CEC_Invitation_to_Participate_with_Excel_Spreadsheets_REFERENCES/NRD

C_Computers_2_ESTAR-NRDC_v6.0_Dataset_v2.xlsx. Retrieved Dec. 12, 2013.

Statistics Canada. 2013. “Canada Population Estimates.” http://www.statcan.gc.ca/start-debuteng.html. Oct. 2013. Retrieved Jan. 30, 2014.

U.S. Census. 2012. State & County QuickFacts. http://quickfacts.census.gov/qfd/states/00000.html. 

Retrieved Jan. 25, 2014.

U.S. Census. 2013. “US Census 2011: Computer and Internet Use in the United States.” May 1, 2013. 

http://www.census.gov/prod/2013pubs/p20-569.pdf. Retrieved Sept. 16, 2013.
Fraunhofer USA Center for Sustainable Energy Systems 34

3.5 Portable Computers

Portable computers includes both laptops (also known as notebooks) and netbook computers (smaller, 

less powerful laptops), but excludes mobile computing devices such as smart phones and tablets. 

3.5.1 Current Energy Consumption

3.5.1.1 Installed Base

We estimate a plugged-in installed base of 93 million portable PCs used in the past month (Nov. 2013). 

The plugged-in installed base measured from CE Usage Survey is 63% of the ownership installed base of 

148 million as reported by CEA (2013a). This is likely due to some portable PCs not being recently used. 

The survey also reports the ownership penetration for portable PCs of 64%, which is similar to other 

sources (see Table 3-16).

Although the estimate of plugged-in penetration of 44% is lower than in our previous report of 62% 

(Fraunhofer 2011), we think that it is accurate, because the 2013 CE Usage Survey included questions to 

distinguish between households that did not own a portable PC and households that have at least one 

but that had not plugged one in within the past month. Therefore, the results provide a richer 

representation of the plugged-in and ownership installed bases.

Table 3-16: Installed base estimates for portable PCs from different data sources.

Year Description Household 

penetration

Households

[millions]

Units/owner

household

Installed Base 

[millions] Source

2013

2013

Portable PCs plugged in last month 45% 53 1.75 93 CE Usage Survey

Portable PC ownership 64%*76 - - CE Usage Survey

2013 Portable PC ownership 65% 77 1.90 148†CEA 2013a

2011 Desktop or Portable PC ownership 76% - - - U.S. Census 2013

2012 Desktop or Portable PC ownership - - 1.80§- A&E 2012

2013 Portable PCs plugged in - - - 93 Representative

* Estimated based on survey responses that indicated no ownership of portable PCs (see Figure 3-12).

† 123.4 million notebook and 24.3 million netbook portable PCs.

§ Based on 61% of Online U.S. adults; 2012 U.S. population as 313.9M, 76.5% of population over 18 years old (U.S. Census 2012); 85% of 

U.S. adults use the Internet (Pew 2013).

† 0 portable PCs plugged in, but ≥1 owned. * Ownership data from (CEA 2013a).

Figure 3-12: Distribution of households by number of portable PCs owned or plugged-in during the past month (Nov. 2013).

According to CEA (2013), netbooks account for 17% of all portable PCs. Although we expect fewer 

netbooks to be used and plugged-in in 2013 due to their declining sales and discontinued production 

0%

10%

20%

30%

40%

Do Not

Own 0† 1 2 3 ≥4

Plugged In 36% 19% 32% 6.6% 2.8% 3.2%

Ownership* 35% 33% 16% 9% 7% Weighted % of U.S. Households
Fraunhofer USA Center for Sustainable Energy Systems 35

(DigiTimes 2012), for an estimate, we use this ratio to compute the annual energy consumption of all 

portable PCs.

Table 3-17: Plugged-In installed base estimates for notebook and netbook portable PCs from the CE Usage Survey.

Type

Households [millions]

Plugged-In [million units]

Not Owned

PCs Plugged-In per Owner Household 

0 1 2 3 ≥4 ≥1†All Primary Second+

Notebook 36 19 32 6.6 2.8 3.2 44 77.7 44 33

Netbook 7 3.8 6.3 1.3 0.6 0.6 8.8 15.3 8.7 6.6

Any Portable 43 23 38 7.9 3.3 3.8 53 93.0 53 40

† Equivalent to the household penetration of plugged-in PCs.

Primary: number of primary PCs.

Second+: number of PCs that are not primary, i.e., secondary, tertiary, etc.; treated as secondary in energy model.

3.5.1.2 Unit Energy Consumption

3.5.1.2.1 Power Draw

We consider the same power draw modes (EPA 2013a) for portable PCs as for desktop PCs in Section 

3.4.1.2: active, short idle, long idle, sleep, and off.

Table 3-18 presents recent power draw estimates for portable PCs. Overall, power draw has decreased

compared to the 2010 estimate (Fraunhofer 2011) by about half for sleep and off modes, and about a 

quarter for idle mode. 

Table 3-18: Power draw estimates for portable PCs from different data sources.

Type Power Draw [W] Year Source Active Short Idle Long Idle*

Sleep Off

Notebook - 14 9.4 1.0 0.5 2012 EPA 2013b†

Notebook - - 10 1.1 0.5 2013 NRDC 2013

Notebook 21 15 - - - 2013 Fraunhofer 2013§

Netbook - 9.1 6.1 0.8 0.5 2012 EPA 2013b†

Any Portable - 14 9.1 1.0 0.5 2012 EPA 2013b†

Any Portable 40 - - 1.1 0 2012 LBNL 2013‡

Any Portable - - 19 2 1 2010 Fraunhofer 2011

* ENERGY STAR v6.0 specification for computers maps the Idle mode of v5.2 as equivalent to Long Idle in v6.0.

† Power draw of each test device in the dataset reweighted based on unit sales of 69% of unit shipments meeting the ENERGY STAR v6.0 

specifications (EPA 2012). Netbook models identified by processor type (10% of dataset).

§ Lab metering of 6 notebook portable PCs.

‡ The field study (with 11 portable PCs) had grouped operational modes as “high power”>10W, “low power”≤10W, and "off"=0W. This 

roughly maps to a combined active, short idle and long idle power draw, sleep, and off power draws, respectively, in the ENERGY STAR v6.0 

specification for computers.

Similar to Section 3.4.1.2, we derive a representative estimate of power draw for different modes with a 

weighted average of newer and older PCs in the total installed base (see Table 3-19).
Fraunhofer USA Center for Sustainable Energy Systems 36

Table 3-19: Determining relative power draw characteristics from age of portable PCs, derived from Figure 3 of (CEA 2014). 

Average age: 2.4 years.

“Older” “Newer”

Year of Purchase 2009 2010 2011 2012 2013

Age [years] ≥4 3 2 1 <1

% of Portable PCs Owned 19% 22% 26% 17% 17%

41% 60%*

Source for Power Draw Model Fraunhofer 2011 EPA 2013b

* Total does not sum to 100% due to rounding.

Several data sources suggest a higher ratio of power draw in active to short idle mode for portable PCs 

than for desktop PCs, e.g., 1.4 for Fraunhofer (2013) and 1.3 for NRDC (2013). Therefore, we apply a 

scaling factor of 1.3 for active-mode power draw relative to short idle mode power draw. Furthermore, 

since Fraunhofer (2011) referred to ENERGY STAR v5.2 (EPA 2009) and does not include a power draw 

estimate for the short idle mode, we apply the same overhead ratio for short idle to long idle (1.5:1) as 

EPA (2013b). 

Unlike a desktop PC, a portable PC may be disconnected from the wall socket and run on its battery. The 

battery will need to be charged with an external power supply (EPS). Therefore, in addition to the 

power modes for desktop PCs (see Section 3.4.1.2), we consider the following additional operational 

modes due to the power draw of the EPS:

 Active + Charging: when the portable PC is actively used and charging its battery.

 Off + Charging: when the portable PC is off and charging its battery.

 Unplugged: when the portable PC is unplugged from its EPS.

 EPS Unplugged: when the EPS is also unplugged from the wall socket. There is no power draw 

(0W) in this “mode.”

DOE (2012) provides an estimate for the power draw of the EPS of notebook and netbook portable PCs

(see Table 3-20). According to the test method for ENERGY STAR v6.0 (EPA 2013b), we consider the EPS 

power draw to already be accounted for when the portable PC is not charging and not unplugged.

Table 3-20: Power draw estimates of the external power supply for portable PCs (DOE 2012), weighted by shipment 

distribution. This excludes the power draw due to the portable PC.

Type

External Power Supply Power Draw [W]

Active*+ 

Charging Active*

Sleep Off + 

Charging Off Unplugged

Notebook 11 4.6 0.8 6.3 0.7 0.7

Netbook 6.6 2.8 0.6 3.8 0.5 0.5

* We consider EPS active mode to correspond to the weighted average of the portable PC 

active, short- and long-idle modes.
Fraunhofer USA Center for Sustainable Energy Systems 37

Figure 3-13: Representative power draw by mode of notebook and netbook portable PCs.

3.5.1.2.2 Usage

A portable PC enters different operational modes depending on whether the user is currently using it, 

how recently it was last used, how the user manually manages its power, its automatic power 

management settings, how often it is charging, and how often it is unplugged from the EPS. We 

compute the time each PC spends in different operational modes using the energy model presented in 

Appendix B.1. Our model draws heavily on the data gathered from the CE Usage Survey where we asked 

U.S. adults about their household use of the most used (primary) portable PC and second-most used 

(secondary) portable PCs. The subsequent subsections explain findings for key aspects of the model in 

more detail.

3.5.1.2.2.1 Usage per Session

We evaluated the active usage of PCs during the day for each session and for the whole day to account 

for the cumulative time portable PCs spend in different operational modes. More specifically, we 

evaluated the usage for different periods of the day (morning and evening) via specific survey questions, 

and inferred usage for weekdays or weekends based on what day “yesterday” was for the survey 

response. We estimate that an average primary portable PC is used about 1.5 times before the evening, 

and about once in the evening. The secondary PC is used about half as much. We found that each 

session lasts about one hour, and is likely somewhat shorter on a weekend than on a weekday.

0

10

20

30

40

Notebook Netbook Any Portable

Active + Charging 36 23 34

Active 30 19 29

Short Idle 23 15 22

Long Idle 15 10 15

Sleep 1.6 1.2 1.6

Off + Charging 6.3 4.1 6.0

Off 0.8 0.8 0.8

Unplugged 0.6 0.5 0.6

Power Draw [W]
Fraunhofer USA Center for Sustainable Energy Systems 38

Primary Portable PC

Secondary Portable PC

Figure 3-14: Average per session usage and number of sessions “yesterday” for primary and secondary portable PCs.

3.5.1.2.2.2 Usage per Day

On average, household occupants actively use portable PCs for 2.8 hours per day, using the primary 

portable PC more than secondary ones (3.4 vs. 2.4 hours), more before the evening than after (1.9 vs. 

1.5 hours for primary), and more during the weekdays than weekends (3.6 vs. 2.8 hours for primary). 

We note that primary desktop PCs have a higher reported active usage per day than primary portable 

PCs (3.9 vs. 3.4 hours).

Primary Secondary

Figure 3-15: Average total usage “yesterday” for primary and secondary portable PCs.

1.0 1.0 1.0

1.1

1.2

0.7

0

1

2

Any Day Week-day Week-end

Per Session Usage [hours]

Pre-Evening Evening

1.5 1.5

1.6

1.1 1.2

1.0

0

1

2

Any Day Week-day Week-end

# Sessions per Day

Pre-Evening Evening

0.8 0.8

0.6

0.9

1.1

0.8

0

1

2

Any Day Week-day Week-end

Per Session Usage [hours]

1.0 0.9

1.0

0.7

0.8

0.6

0

1

2

Any Day Week-day Week-end

# Sessions per Day

0

1

2

3

4

5

Any Day Weekday

Weekend

Evening 1.5 1.7 1.0

Pre-Evening 1.9 1.9 1.8

Whole Day 3.4 3.6 2.8

h/day

0

1

2

3

4

5

Any Day Weekday

Weekend

Evening 1.1 1.4 0.2

Pre-Evening 1.3 1.3 1.1

Whole Day 2.4 2.7 1.3

h/day
Fraunhofer USA Center for Sustainable Energy Systems 39

3.5.1.2.2.3 Power Management

PC energy consumption can be reduced through power management. The user may do so manual 

routines of power management (e.g., by putting the PC to sleep at night), or by enabling automatic 

power management (PM) settings (e.g., auto-hibernate to have the computer save its state and 

automatically turn off after a chosen period of inactivity). We discuss these two manual and automatic 

power management methods in the next section.

Manual Power Management

We asked U.S. adults how often they manually turned off their PC or put it to sleep. Our survey results 

indicated that users tend to manually turn off their portable PCs (60% of the time during the day and 

65% at night), while leaving them on for 19% of the time during the day. Portable PCs are manually put 

to sleep 21% of the time during the day. However, even if the PC is left on, automated PM can place the 

PC in a low-power mode. Relative to desktop PCs (see Section 3.4), users turn off a higher portion of 

portable PCs (e.g., 60% vs. 40%) during the daytime.

Daytime Night

* Responses estimated based on ratio between Left On and 

Sleep for daytime.

Figure 3-16: Portion of users manually setting portable PCs into various power modes for the daytime or nighttime.

Automatic Power Management 

We infer automatic power management (PM) settings using the method described in . This indicates 

that most portable PCs have some level of PM enabled (94%), particularly with auto-screen off (52%),

which engages the long idle mode, followed by auto-screen off (29%) where the PC enters short idle 

mode. Relative to desktop PCs (see Section 3.4), portable PCs have a higher rate of PM enabling (63 vs. 

38% with auto-sleep or auto-hibernate enabled).

Figure 3-17: Percentage of portable PCs with various automatic PM modes enabled.

20% 18% 19%

20% 22% 21%

61% 60% 60%

0%

20%

40%

60%

80%

100%

Primary Secondary Any Portable

% of Users with Manual 

Power Management

Off

Sleep

Left On

16% 18% 17%

16%

22% 18%

69%

60% 65%

0%

20%

40%

60%

80%

100%

Primary Secondary Any Portable

Off

Sleep*

Left On*

13% 13% 13%

48% 55% 52%

33% 27% 29%

6% 6% 6%

0%

20%

40%

60%

80%

100%

Primary Secondary Any Portable

% Desktop PCs in Power 

Management Mode

PM Disabled

Auto-Screen Off

Auto-Sleep

Auto-Hibernate
Fraunhofer USA Center for Sustainable Energy Systems 40

3.5.1.2.2.4 Time in Operational Modes

A portable PC enters different power modes depending on whether or not the user is currently using it, 

how recently it was last used, how the user manually manages its power, and its automatic PM settings. 

As with desktop PCs, we compute the time each PC spends in different power modes using the energy 

model presented in Appendix B.1. However, we use shorter default time thresholds for lower power 

modes to be triggered, i.e., 10 vs. 15min for short idle and 25 vs. 30min for long idle (values empirically 

determined from the ENERGY STAR qualified product list (EPA 2013c); see Appendix section B.1.2 for 

more details). Furthermore, because we do not have reliable data differentiating the usage time of

netbooks and notebooks, we assume that notebooks and netbooks spend equal portions of time in 

different power modes.

To estimate the time portable PCs spend charging or unplugged, we draw on the DOE (2012) EPS and 

battery charger rulemaking analysis (see Table 3-21). Specifically, we re-scale our time estimates from 

the CE Usage Survey by applying ratios for the times charging to not charging, and unplugged to 

plugged.

Table 3-21: Time usage estimates of portable PC EPSs from DOE (2012). Weighted average by shipment distribution of the 

reference case.

Type

Time of Day [%] in Operational Mode

Active*+ 

Charging Active*

Sleep Off + 

Charging Off Unplugged†

EPS Unplugged

Notebook 2.5% 17% 13% 3.1% 48% 0.0% 16%

Netbook 3.4% 14% 3.6% 0.0% 54% 0.0% 25%

* The portable PC is plugged in to the charger in this mode. We consider the EPS active mode to correspond to the 

weighted average of the portable PC active, short idle, and long idle modes.

† Note that the reference case assumes no time spent with the portable PC unplugged from the EPS.

Figure 3-18 shows the average amount of time each portable PC spent in different operational modes. 

Portable PCs spend a large majority of time in sleep and off modes (77%) mainly due to manual PM or 

automatic powering down after each session of use. Table 3-22 shows our results for the portion of time 

spent in Active + Idle modes; they broadly agree with other studies on residential PC use.

Compared to desktop PCs, portable PCs spend more time in lower power modes (19 vs. 16 hours in 

sleep, off, or EPS unplugged modes), less time in short and long idle modes (2.0 vs. 4.2 hours), and less 

time in active mode (2.9 vs. 3.4 hours). This is due to portable PCs, being manually put into low power 

modes more frequently, having more aggressive automated PM settings, and lower power modes 

triggering after shorter time thresholds. Portable PCs also spend 2.0 hours charging (in both Active and 

Off modes), but are unplugged from the EPS for 3.3 hours a day on average.
Fraunhofer USA Center for Sustainable Energy Systems 41

‡ Our model defines night as when the household has gone to sleep, so we assume no active usage.

* Note that usage time for charging is already counted in usage times for active and off modes, so that does not count 

towards the total time plugged in.

Charging (Active): time spent charging while in active mode.

Charging (Off): time spent charging while in off mode.

Figure 3-18: Average time spent in various operational modes in one day (left) and in one year (right) for portable PCs.

Table 3-22: Comparison of percentage of time notebook PCs spent in various operational modes with other data sources.

Time [%] in Operational Mode

Active Year Setting Source *Short Idle Long Idle Active + Idle†Sleep Off**

14% 2.6% 6.9% 23% 29% 48% 2013 Residential CE Usage Survey

- 16% - 16% 42% 42% 2012 Residential LBNL 2013‡

18% - 15% 33% 25% 42% 2010 Residential Fraunhofer 2011

- 35% 15% 50% 5% 45% 2013 Office ENERGY STAR v6.0 (EPA 2013a)§

- - 40% 40% 5% 55% 2009 Office ENERGY STAR v5.2 (EPA 2009)§

41% - - 41% 48% 20% 2008 Office Microsoft 2008

* Includes active + charging time.

** Includes charging (off) and unplugged, but excludes EPS unplugged time.

† Combined active and idle.

‡ Field measurement with a small sample size of 11 portable PCs.

§ ENERGY STAR Typical Energy Consumption values are based on studies of computer usage in office buildings (ECMA 2010, Microsoft 2009).

3.5.1.3 Unit Energy Consumption and Annual Energy Consumption

We compute the energy consumption by multiplying the time a PC spends in each power mode by the 

average power draw in that mode. Figure 3-19 shows the energy consumption for each day period due 

to the time in various operational modes. Active usage accounts for a considerable amount of energy 

consumption (57%), followed by long idle (15%), then short idle (8.2%). Lower power modes account for 

6.6% and 5.5% of UEC, for sleep and off modes, respectively. Charging accounts for 7.7% of UEC.

Netbook PCs have considerably lower power draw values than notebook PCs for the active, short idle, 

and long idle modes (19 vs. 30W, 15 vs. 23W, 10 vs. 15W, respectively) , resulting in a 33% lower UEC for 

netbooks.

0

4

8

12

16

20

24

Whole

Day

PreEvening Evening Night‡

Charging(Active)* 1.5 0.7 0.4 0.3

Charging (Off)* 0.5 0.2 0.1 0.2

Off 9.9 3.7 2.1 4.1

Sleep 6.0 2.7 1.5 1.9

LongIdle 1.4 0.6 0.3 0.5

ShortIdle 0.5 0.3 0.2 0.1

Active 2.9 1.6 1.3 0.0

Total Plugged In 21 8.8 5.3 6.5

h/day

0

2,000

4,000

6,000

8,000

All Days Weekdays

Weekends

Charging(Active)* 538 402 133

Charging (Off)* 184 126 58

Off 3,417 2,347 1,082

Sleep 2,202 1,561 645

LongIdle 452 385 58

ShortIdle 168 123 45

Active 900 702 189

Total Plugged In 7,861 5,647 2,210

h/yr
Fraunhofer USA Center for Sustainable Energy Systems 42

‡ Our model defines night as when the household has gone to sleep, so we assume no active usage then.

* Only accounting for energy sole due to charging while in active and off modes.

Figure 3-19: Total energy consumed in various operational modes in one day and in one year for portable PCs. Weighted 

average across primary and secondary notebook and netbook portable PCs.

Our calculations yield a UEC of 53 kWh/year for a typical portable PC and an AEC of 4.9 TWh/year. This 

reflects a conservative estimate that the same proportion of netbooks of all portable PCs is plugged in 

and used as the proportion owned. However, declining netbook sales (CEA 2013b) suggest a decrease in 

their use. If we assumed that the installed base of portable PCs consisted entirely of notebooks, i.e., 

included no netbooks, this would yield an AEC of 5.1 TWh/year. Furthermore, while the installed base 

for portable PCs exceeds that of desktop PCs (93 vs. 88 million), their AEC is lower (4.9 vs. 16 TWh/year), 

because they have a 72% lower UEC (53 vs. 186 kWh/year).

Table 3-23: Unit energy consumption (UEC), installed base, and annual energy consumption (AEC) of portable PCs.

Type

UEC [kWh/yr] Installed Base

[millions]

AEC

Charging Active Short Idle Long Idle Sleep Off Total [TWh/yr]

Notebook 4.3 31 4.5 8.1 3.6 3.0 55 78 4.3

Netbook 2.9 20 2.9 5.2 2.7 2.5 37 15 0.6

Total/Wt.Avg. 4.1 30 4.4 7.8 3.5 2.9 53 93 4.9

3.5.2 Comparison with Prior Energy Consumption Estimates

We found a decrease in the both portable PC UEC and AEC from 2010. A major reason is the drop in 

plugged-in installed base (132 to 93 million) driven by a sharp decrease in the market share of portable 

PCs in the overall market for desktop PCs, portable PCs, and tablet computers (from 57% in 2010 to 

about 21% in 2013, CEA 2013b). To a large extent, this reflects around a ten-fold increase in the 

household ownership penetration of tablets, from 4% (Fraunhofer 2011) to 39% (CEA 2013a). This same 

trend could also explain the decrease in active use time that we found. 

We refined our computer usage survey from 2010, and believe that it increases the accuracy of our 

estimates for time in operational modes for portable PCs. See Section 3.5.2 for a discussion on various 

refinements. In addition, for portable PCs our model explicitly calculates the power draw, time in 

modes, and energy consumption due to the external power supply (charging, unplugged, etc.).

0

25

50

75

100

125

150

Whole

Day

PreEvening Evening Night‡

Charging* 11.2 5.1 3.1 3.0

Off 7.9 3.0 1.7 3.3

Sleep 9.6 4.3 2.3 3.0

Long Idle 21 9.2 4.8 7

Short Idle 12 5.6 4.0 2.4

Active 83 46 37 0.0

ALL 145 73 53 19

Wh/day

0

15

30

45

60

All

Days

WeekdaysWeekends

Charging* 4.1 3.0 1.1

Off 2.9 2.0 0.9

Sleep 3.5 2.5 1.0

Long Idle 7.8 6.7 1.0

Short Idle 4.4 3.2 1.2

Active 30 24 6.4

ALL 53 41 12

kWh/yr
Fraunhofer USA Center for Sustainable Energy Systems 43

Table 3-24: Current and prior energy consumption estimates for portable PCs.

Year Units

[millions]

Power Draw [W] Time in Mode [hr/yr] PM*

Enabled

UEC

[kWh/yr]

AEC

[TWh/yr] Source Active Sleep Off Active + Idle Sleep Off

2013 93 29a1.6 0.8b1,770‡2,190 3,602§64% 53 4.9 Current

2010 128 19 2 1 2,915 2,210 3,635 69% 63 8.3 Fraunhofer 2011

2009 76 - - - - - - - 43 3.1 CCAP 2009††

2006 39 25 2 2 2,368 935 5,457 40% 72 2.8 TIAX 2007

2005 36 25 2 2 2,368 935 5,457 40% 72 2.6 TIAX 2006

2001 16.6 - - - - - - - 77 1.3 RECS 2001

2001 17.3 15 3 0

‡‡ 1,007 651 7,102 - - - LBNL 2004

1999 16 15 3 2 521 261 7,978 100% 9 0.14 LBNL 2001

* Percent of computers with power management enabled (auto-sleep or auto-hibernate, not including auto-screen off).

† Weighed average of power draw for active, short idle, and long idle modes.

§ Estimate for time in off mode excludes time unplugged from EPS.

‡ Combined time in active, short idle, and long idle modes.

†† Data for office equipment only.

‡‡ Disconnected.

a 30 W weighted average if charging included.

b 1.1 W weighted average if charging included.

3.5.3 References

ATUS. 2012. “American Time Use Survey — 2012 Microdata Files.” Jun. 20, 2013. United States 

Department of Labor. http://www.bls.gov/tus/datafiles_2012.htm. Retrieved Oct. 30, 2013.

CEA. 2010. “12th Annual household CE Ownership and Market Potential.” CEA Market Research Report. 

Consumer Electronics Association. May, 2010. Consumer Electronics Association.

CEA. 2013a. “15

th Annual CE Ownership and Market Potential Study.” CEA Market Research Report, 

April, 2013. Consumer Electronics Association.

CEA. 2013b. “U.S. Consumer Electronics Sales & Forecasts 2009-2014.” CEA Market Research Report, 

July, 2013. Consumer Electronics Association.

Digitimes. 2012. Chen, M. and J. Tsai. “Intel may need to adjust roadmap for PC-use Atom Processors.” 

Sept. 3, 2012. http://www.digitimes.com/news/a20120903PD208.html. Retrieved Feb. 6, 2014.

DOE. 2012. “Rulemaking for Battery Chargers and External Power Supplies Energy Conservation 

Standard. Energy Use Analysis Spreadsheet.” Feb. 17, 2012.

http://www.regulations.gov/#!documentDetail;D=EERE-2008-BT-STD-0005-0084. Retrieved Feb. 6, 

2014.

EPA. 2012. “ENERGY STAR Unit Shipment and Market Penetration Report 2012.” December, 2012. 

http://www.energystar.gov/ia/partners/downloads/unit_shipment_data/2012_USD_Summary_Repo

rt.pdf. Retrieved Sept. 16, 2013.

EPA. 2013a. “ENERGY STAR Program Computer Specification Version 6.0.” Sept. 12, 2013. 

http://www.energystar.gov/products/specs/computer_specification_version_6_0_pd. Retrieved Dec. 

12, 2013.

EPA. 2013b. “ENERGY STAR Computers Draft 2 Version 6.0 Dataset.” May 15, 2012. 

https://www.energystar.gov/products/specs/system/files/Computers_Draft_2_Dataset_masked.xlsx. 

Retrieved Sept. 16, 2013.

FhCSE. Urban, Bryan, Kurt Roth, and Verena Tiefenbeck. 2011. “Energy Consumption of Consumer 

Electronics in U.S. Homes in 2010.” Final Report to the Consumer Electronics Association. 
Fraunhofer USA Center for Sustainable Energy Systems 44

http://www.ce.org/CorporateSite/media/Government-Media/Green/Energy-Consumption-of-CE-inU-S-Homes-in-2010.pdf. Dec.

LBNL. 2013. Greenblatt, J. B. 2013. “Field data collection of miscellaneous electrical loads in Northern 

California: Initial results.” Lawrence Berkeley National Laboratory. LBNL Paper LBNL-6115E. Jul. 22, 

2013. http://escholarship.org/uc/item/5cq425kt. Retrieved Sept. 16, 2013.

NRDC. 2013. “NRDC’s Response to CEC’s Invitation to Participate in the Development of Appliance 

Energy Efficiency Measures. NRDC Computers Attachment 2. ENERGY STAR v6.0 Dataset v2 with 

additions from NRDC.” May 9, 2013.

http://www.energy.ca.gov/appliances/2013rulemaking/documents/responses/Consumer_Electronic

s_12-AAER2A/NRDC_Response_to_CEC_Invitation_to_Participate_with_Excel_Spreadsheets_REFERENCES/NRD

C_Computers_2_ESTAR-NRDC_v6.0_Dataset_v2.xlsx. Retrieved Dec. 12, 2013. 

Pew. 2012. “Adult gadget ownership over time.” Pew Internet surveys 2006-2013. April, 2012. 

http://www.pewinternet.org/Trend-Data-(Adults)/Device-Ownership.aspx. Retrieved 30 Oct. 2013.
Fraunhofer USA Center for Sustainable Energy Systems 45

3.6 Home Audio: Shelf/Compact Audio and Speaker Docks

The home audio products evaluated in further detail include speaker docks and shelf stereo systems, 

also called Mini or Compact stereo systems. A speaker dock has a plug-in connection for an MP3 player, 

smartphone, or tablet. An ordinary speaker dock includes two speakers rated at about 5 W each, a 

docking station, and sometimes a clock and a tuner (see Figure 3-20, left). Some speaker dock models 

include more than two speakers and a subwoofer, and may draw about 100 W in active mode. 7

A shelf stereo system consists of a central component with one or more media players (e.g., CD/DVD, 

radio tuner, and docking station for an MP3 player, smartphone or tablet), two or more detached 

speakers, and sometimes a subwoofer (see Figure 3-20, right). 

Figure 3-20: Example of a speaker dock (left), and shelf stereo system (right), source: iHome, Sony.

3.6.1 Current Energy Consumption

3.6.1.1 Installed Base

According to the CE Usage Survey data, 45% of households have a speaker dock and 46% have a shelf 

stereo system. Multiplied by the average number of devices per household, this yields installed bases of 

98 and 64 million respectively (see Table 3-25). We were unable to find data on the installed base of 

speaker docks and shelf stereo systems by rated power draw levels. 

Table 3-25: Installed base of speaker docks and shelf stereo systems (CE Usage Survey).

Home Audio System Installed Base

[millions]

Household 

Penetration

Number of devices

per Household Source

Speaker dock 98 45% 1.8 CE Usage Survey

Shelf stereo system 64 46% 1.2 CE Usage Survey

3.6.1.2 Unit Energy Consumption

3.6.1.2.1 Power Draw

Speaker dock and shelf stereo systems can be characterized by the following three operating modes:

 Active – Device is actively being used, playing music or other audio content

 Active standby – Device is neither playing audio content, nor turned off manually

 

7

Examples include the B&W Zeppelin Air (B&W Zeppelin Air-Specifications 2013) and JBL OnBEAT Xtreme (JBL OnBEAT Xtreme Owner’s Manual 

2011). 
Fraunhofer USA Center for Sustainable Energy Systems 46

 Standby – Device is turned off manually but remains plugged in. Some devices have Autopower down (APD) function and automatically enter a standby mode after a defined period 

of time (usually between 15 and 30 minutes). 

Audio manufacturers use several terms to quantify the power of audio systems, such as peak power, 

total system output power, and continuous power. All of these usually quantify the maximum or peak 

power output, and do not accurately characterize the average active power draw of an audio system, 

which is much lower than the values in audio system specifications. Many product specifications also 

include a “power consumption” value; the test procedure to determine these values is not stated. Based 

on measurements8of three best-selling9speaker docks, we found that the actual operating power draw 

(~5W) equals approximately half of the “power consumption” values provided in product specifications. 

We did not measure speaker docks with high total output, as they were not sold in the store where we 

performed the measurements. Instead, we scaled the total output power to actual power by applying 

the same scaling factor (8) found for three shelf stereo systems that we measured. This suggests that 

speaker docks with a total output power of 100 and 120W would draw approximately 13 and 15 W, 

respectively, in active mode.

Unfortunately, we could not find data for the portion of the installed base of speaker docks with higher 

power draw. Nevertheless, we expect that the penetration of these speaker dock systems is likely very 

low. Notably, these speaker docks are not among “best selling” products listed on leading CE retailers 

such as Amazon.com and BestBuy.com. Second, these audio systems often cost much more than most 

speaker docks, typically between $300 and $600.

10 For these reasons, we did not include these models 

in the final power draw calculations. Nonetheless, the large difference in power draws between typical 

and high-power speaker docks makes the average power draw of speaker docks somewhat sensitive to 

the penetration of high-power devices. For example, if 5% of the speaker dock installed base drew 15W 

(total output system power 100 -120W) in active mode, that would increase the UEC in active mode by 

about 7%. The market share of high-power speaker docks and their actual power draw levels warrant 

further study.

After reviewing product documentation (e.g. owner’s manual, product specification, etc.) for shelf 

stereo systems11, we found that these products have total system power outputs from 40 to 700 W. To 

estimate the typical power draw of shelf stereo systems, we measured the power draw of three of the 

most popular mini-shelf stereo systems with total output powers of 220, 500, and 700 W while playing a 

CD with the volume set at minimum, medium and maximum levels. We found that the average activemode power draw of three mini-shelf stereo systems with a total output power exceeding 200 W was 

less than 20 W for all systems except for one that exceeded that level at maximum volume (see Figure 

3-21). 

 

8 We measured the average power draw at min., middle, and max. volume while playing music and took the average.

9

Top 10 best-selling models on Amazon.com and bestbuy.com.

10 The price for speaker docks we measured varies between 60 and 80 US dollars.

11 Based upon reviews of products from LG, Panasonic, Samsung, Sony, and Yamaha.
Fraunhofer USA Center for Sustainable Energy Systems 47

Figure 3-21: Active power draws of different mini-shelf stereo systems (Fraunhofer measurements).

Our measurements of standby power draw for speaker docks averaged 1.3 W, while those for mini-shelf 

stereo systems did not exceed 0.5W. We found different ways of putting stereo systems into standby 

mode. First of all, it can be achieved by using the “sleep” function which allows system to enter standby 

mode after defined period of time. This defined period of time usually vary from 10 to 90 minutes and 

set up by default to the maximum. Secondly, switching a stereo system off manually will also allow it to 

enter the standby mode. Lastly, two of three systems we measured had auto-power down, which puts 

the system into standby mode after a defined period of time12. We did not find a correlation between 

total output power draw and standby power draw. 

Based on these data, we estimate the average power draw by mode values shown in Table 3-26. The 

power draw values in both active- and standby-modes were calculated using a weighted average of pre2010 (92%) and post-2010 systems (8%, CEA 2013). The active power draw for pre-2010 systems comes 

from Bensch et al. (2010) and the active power draw for post-2010 system were calculated based on our 

measurements 2013 as weighted average based on the system’s popularity on the market. Since we did 

not find active standby power draw measurements for post-2010 shelf stereo systems, we used the 

average of our power measurements of post-2010 systems.

Table 3-26: Power draw by mode for audio systems

Audio System Power [W] Sources Active Active Standby Standby

Speaker dock 5 3 1.3 Fraunhofer measurements

Shelf stereo system 30 12 4.0 FhCSE 2011, Fraunhofer measurements

3.6.1.2.2 Usage 

We evaluated speaker dock and shelf stereo system usage through the CE Usage Survey (see Figure 

3-22, left). Based on all responses, we estimated that the average speaker dock spends 3.3 hours per day 

in active mode (see Table 3-27). The data also indicate that 66% of U.S. adults turn their speaker dock 

off with a power switch or remote control after they finish using it. Only 6% leave their speaker dock 

always on and 11% responded that their speaker dock does not have a power switch13. 

 

12 Usually between 15 and 25 minutes.

13 We treated these responses as people who never turn off their speaker docks

0

20

40

60

System A

700 W

System B

500 W

System C

220 W

System A

700 W

System B

500 W

System C

220 W

Active CD Active Tuner

Max

Min

Mean

W
Fraunhofer USA Center for Sustainable Energy Systems 48

Figure 3-22: Frequencies of responses regarding the active daily usage of speaker systems.

A review of product documentation revealed that some speaker dock systems have an auto powershutdown (APD) feature that automatically places the system into standby mode after about 20 minutes 

of inactivity (e.g. Sony 2013a, Samsung 2013, Sony 2013b). The U.S. adults’ replies indicate that nine 

percent of speaker docks have the APD feature and eight percent answered “don’t know”.

The CE Usage Survey found similar usage for mini-shelf stereo systems (see Figure 3-22, right), and the 

average time spent listening to music or other audio is 3.4 hours a day. Eighty-six percent of U.S. adults 

answered that they turn their shelf stereo system off manually using a power switch or remote control. 

Only four percent of mini-shelf stereo systems reported having APD. This is generally consistent with the 

portion of the installed base accounted for by post-2010 shelf stereo models (8%), which would be the 

units most likely to have APD functionality.

Table 3-27: Annual usage by mode of speaker dock and shelf stereo systems

Home Audio System

Usage [h/year]

Active Active standby Standby Sources

Speaker dock 1,205 2,007 5,548 CE Usage Survey

Shelf stereo system 1,241 949 6,570 CE Usage Survey

The ENERGY STAR specification version 3.0 for Audio Products that came into effect in May, 2013 

requires qualifying devices to have a default APD setting of two hours, maximum. Thus, the time spent 

in active standby mode by very new ENERGY STAR devices might be smaller. We do not, however, have 

data on the market penetration of ENERGY STAR speaker dock and shelf stereo systems for 2013. 

3.6.1.2.3 Unit Energy Consumption

Our calculation for speaker dock system UEC yields 19 kWh/year, with no mode accounting for a 

majority of the UEC. The UEC of a mini-shelf stereo system equals 75 kWh/year, with 51% and 34% of 

UEC occurring in active and standby mode, respectively. See Table 3-28 and Figure 3-23. Although the 

newer mini-shelf stereo systems draw less than 0.5 W in standby mode, a large installed base of pre2010 unit (92% of units) results in an average 4 W power draw in standby mode. 

0%

10%

20%

30%

40%

50%

0 1 2 3 4 5 6 7 8 9 10+

Hours in Active Mode per Day

Speaker Dock

0%

10%

20%

30%

40%

50%

0 1 2 3 4 5 6 7 8 9 10+

Hours in Active Mode per Day

Shelf Stereo
Fraunhofer USA Center for Sustainable Energy Systems 49

Table 3-28: UEC calculation for speaker systems.

Speaker Dock Shelf Stereo

Power

[W]

Usage 

[hr/yr]

UEC

[kWh/yr]

Power

[W]

Usage 

[hr/yr]

UEC

[kWh/yr]

Active 5 1,205 6.0 30 1,241 38

Active Standby 3 2,007 6.0 12 949 11

Standby 1.3 5,548 7.2 4.0 6,570 26

Total - 8,760 19.2 - 8,760 75

Figure 3-23: Speaker dock UEC distribution among different modes

3.6.1.3 Annual Energy Consumption

Speaker dock and mini-shelf stereo systems consumed approximately 2.0 and 5.0 TWh respectively, in 

2013 (Table 3-29).

Table 3-29: AEC summary for speaker systems.

Audio System UEC 

[kWh/yr]

Installed Base 

[millions]

AEC 

[TWh]

Speaker dock 19 98 1.9

Shelf stereo system 75 64 4.8

3.6.2 Comparison with Prior Energy Consumption Estimates

Our prior study (FhCSE 2011) estimated that speaker docks consumed 1.2TWh in 2010 (see Table 3-30). 

Thus, our current estimate for speaker dock AEC is more than 50 percent higher despite a decrease in 

average active-mode power draw. This largely reflects that the installed base has more than doubled 

since 2010. Although the active-mode usage estimate has increased by about 50 percent, it is not clear 

how real this effect is, since the current usage estimates are more refined than those for 2010.

In contrast, the estimated AEC of mini-shelf stereo systems has decreased 27% since 2010. This primarily 

reflects about a 50 percent decrease in estimated active usage in 2013 relative to 2010. We believe that 

the 2013 usage estimates are more accurate, as they are based on several hundred survey responses 

and closer to survey-based usage estimates for 2006. In contrast, the 2010 usage estimates comes from 

field monitoring of a small number (15) of systems. 

31%

50%

31%

15%

37%

35%

0

20

40

60

80

Speaker Dock Shelf Stereo

Off

Standby

Active

kWh/year
Fraunhofer USA Center for Sustainable Energy Systems 50

Table 3-30: Prior energy consumption estimates for speaker docks.

Power [W] Usage [h/yr]

Year Units 

[millions] Active Active Standby Standby Active Active Standby Standby UEC[kWh/yr]

AEC

[TWh/yr] Source

2013 98 5 3 1.3 1,205 2,007 5,548 19 1.9 Current

2010 48 10 3 NA 800 100 7,860 25 1.2 FhCSE 2011

Table 3-31: Prior energy consumption estimates for mini-shelf stereo system.

Power [W] Usage [h/yr]

Year Units 

[millions] Active Active Standby Standby Active Active Standby Standby UEC[kWh/yr]

AEC

[TWh/yr] Source

2013 64 30 12 4.0 1,241 949 6,570 75 4.8 Current

2010 63 32 NA 4.3 2,482 NA 6,278 105 6.6 Bensch et al. 2010

2006 76 23 16 7.0 840 730 7,190 81 6.2 TIAX 2007

3.6.3 References

Bensch, I., S. Pigg, K. Koski and R. Belshe. 2010. “Electricity Savings Opportunities for Home Electronics 

and Other Plug-In Devices in Minnesota Homes – A technical and behavioral field assessment.” Final 

Report by the Energy Center of Wisconsin. ECW Report 257-1. http://www.state.mn.us/mn/ 

externalDocs/Commerce/CARD_Plugging_into_Savings_Study_052710014507_MN_Home_Elect_Dev

ices.pdf. May.

Bowers & Wilkins. 2013. “Zeppelin Air-Specifications.” http://www.bowers-wilkins.com/Wireless-MusicSystems/Wireless-Music-Systems/Zeppelin-Air/product-details.html#productSpec. 

CEA S&F. 2013. “U.S. Consumer Electronics Sales & Forecasts 2009-2014.” CEA Market Research Report. 

Consumer Electronics Association. Jul.

EPA. 2013. ENERGY STAR program requirements Audio/Video. Version 3.0. Environmental Protection 

Agency. http://www.energystar.gov/ia/partners/prod_development/revisions/downloads/ 

audio_video/Final_Version_3_AV_Program_Requirements.pdf?5c24-7fe5 May.

FhCSE. Urban, Bryan, Kurt Roth, and Verena Tiefenbeck. 2011. “Energy Consumption of Consumer 

Electronics in U.S. Homes in 2010.” Final Report to the Consumer Electronics Association. 

http://www.ce.org/CorporateSite/media/Government-Media/Green/Energy-Consumption-of-CE-inU-S-Homes-in-2010.pdf. Dec.

JBL. 2011. “OnBEAT Xtreme Owner’s Manual.”

http://www.jbl.com/images/media/ONBEATXT_OM_EN.pdf

Roth, K. and K. McKenney. 2007. “Energy Consumption by Consumer Electronics (CE) in U.S. 

Residences.” Final Report by TIAX LLC to the Consumer Electronics Association. Dec.

Samsung 2013. Wireless Audio with Dock. User Manual for DA-E570.

Sony. 2013a. Reference Guide for ICFCS515IP personal audio docking system. Ref. 4-286-722-15(1)

Sony. 2013b. Reference Guide for RDPM15IP personal audio docking system. Ref. 4-274-302-22(1)
Fraunhofer USA Center for Sustainable Energy Systems 51

3.7 Monitors

3.7.1 Current Energy Consumption

The computer monitors category includes displays that must be plugged into a computer, such as 

external or stand-alone monitors. It excludes integrated displays, such as those built into laptop 

computers or all-in-one PCs, as well as multimedia projectors. 

3.7.1.1 Installed Base

We estimate an installed base of 97 million monitors in 2013 (see Table 3-32) based on the CE Usage 

Survey (Appendix A). U.S. adults were asked how many monitors were plugged into the two most-used 

desktop and portable computers, producing the distributions in Figure 3-24. We estimate that 42% of all 

households had at least one monitor (68% of households with a computer).

Table 3-32: Installed base of monitors.

Computers 

[millions]

Monitors per

Computer

Monitors

[millions]

Desktop primary 53 0.9 47

Desktop secondary 10 0.8 8

Portable primary 53 0.2 13

Portable secondary 15 0.1 2

Other*50 0.5 27

Total/Average 181 0.5 97

* Refers to desktop and portable computers that are not primary and secondary, 

i.e. tertiary, quaternary, etc.

Figure 3-24: Installed base of monitors and computers.

We found a 26 percent decline in the installed base of external monitors since 2010 (FhCSE 2011). 

Similarly, monitor sales decreased 24% from 2010 to 2013 (Display Search 2014). As shown in Figure 

3-25, 27% of desktop computers in 2013 had no external monitor, about 10% higher than in 2010. The 

portion of desktop and portable computers with at least one external monitor decreased by 13% and 9%

(absolute), respectively, from 2010 to 2013. One reason for the decrease in the number of external 

monitors associated with desktop PCs is the increase in the installed base of all-in-one PCs, i.e., those 

with integrated displays. Their cumulative sales14 equaled about 18 million from 2007 to mid-2013 

(FhCSE 2011, Display Search 2013, 2013 CE Usage Survey ), or about 21% of all plugged-in desktop 

computers in 201315 relative to 14% of desktops circa 2010. 

 

14 We did not find estimates for the fraction of all-in-one PCs sold to consumers; however, we assumed that AIO computers were mostly 

purchased for in-home use.

15 We estimate an installed base of 88 Million desktop computers plugged in 2013 (see Section 3.4).

88 93

78

20

0

20

40

60

80

100

Desktop PC Portable PC

Millions

Computers Monitors
Fraunhofer USA Center for Sustainable Energy Systems 52

Figure 3-25: Distribution of monitors per desktop and portable computer.

3.7.1.2 Unit Energy Consumption

3.7.1.2.1 Power Draw

Monitors have three primary power modes: active, sleep, and off. Active mode occurs whenever the 

monitor is on and displays an image. Monitor active-mode power draw depends most strongly on 

display technology, screen size, and default settings from manufacturer (e.g., brightness and contrast).

In addition, display resolution can also affect active-mode power draw. Sleep mode is a low-power state 

entered after a period of inactivity, typically 15 minutes, when power management (PM) is enabled (see 

Appendix B.1.2). User input from a keyboard or mouse awakens a sleeping monitor to active mode. Off 

mode is the lowest plugged-in power mode and is entered when the user powers down the monitor by 

manually switching it off or the computer’s power settings are set for auto turn off the display. 

The CE Usage Survey (see Appendix A) shows that LCDs dominate the installed base of monitors, 

accounting for 83 percent of the installed base. 16 Thus, the portion of CRT monitors has not changed

appreciably since 2010 (Table 3-33). The average display size of the installed base has increased to 20.9 

inches17 in 2013 (NPD DisplaySearch 2012), compared to 18 inches in 2010 (FhCSE 2011) and 17 inches in 

2006 (TIAX 2007). Figure 3-26 shows the estimated size distribution of the installed base of LCDs. 

Figure 3-26: Distribution of LCD monitors installed base in 2013 by diagonal screen size (FhCSE 2011, DisplaySearch 2014).

We also found about a seven-fold increase in the installed base portion of LCD monitors with LED 

backlights, from 10% in 2010 (Kim & Semenza 2012) to 2013 69% (IDC 2013; This change also influences 

 

16 Since monitor responses were given only for up to two desktop and portable computers, we assumed the proportions of LCD and CRTs were 

the same for less-used computers. In the limiting case, i.e., if all monitors for computers three and beyond were CRTs, the split would shift to 

60% LCD and 40% CRT. For reference, CEA (2014) estimated there were 35 million CRT monitors in U.S. households in February 2014, including 

units not plugged in (e.g., in storage).

17 Projected screen size for 2013.

27%

64%

8%

1% 1%

0%

20%

40%

60%

80%

100%

0 1 2 3 4+

Monitors per Computer

Desktop PC

2010 2013

85%

13%

2% 0% 0%

0%

20%

40%

60%

80%

100%

0 1 2 3 4+

Monitors per Computer

Portable PC

2010 2013

59%

18% 22%

2% 0.1%

0%

20%

40%

60%

80%

100%

15"-19" 20"-21" 22"-24" 25"-29" 30"-34"

2010 2013

LCD Monitors 

by screen size

Average Size: 20.9"
Fraunhofer USA Center for Sustainable Energy Systems 53

the average active-mode power draw (see Figure 3-28). On average, an LCD monitor with LED backlight 

draws about 30% less power than one with a CCFL backlight, and this difference increases with diagonal 

size (ENERGY STAR 2013, Fraunhofer measurements 2013, Dell 2013, Cnet 2010a, Cnet 2010b). 

For this study, we assume that all monitors purchased before 2006 have been retired. Since monitors 

with LED backlights only began to have a significant market share in 2011, we divide the installed base 

into pre- and post-2010 models. Adjusted18 industry sales data (Display Search 2014) show that 27 

million LCD displays were shipped to U.S. consumers between 2011 to mid-2013, and that 63% of these 

monitors have LED backlights (see Figure 3-27).

Figure 3-27: Portion of monitor sales by backlight technology (DisplaySearch 2014).

For all CRT monitors and 2006-2010 LCDs, we used power draw characteristics from the previous CE 

study (FhCSE 2011). For post-2010 LCDs, we assumed that all LCD-LED monitors met the ENERGY STAR

specification and used the average power draw values for each size range from the ENERGY STAR

Displays Product List (2013). For LCD- CCFLs, we divided them among ENERGY STAR and non-ENERGY 

STAR units. Since LCD-LEDs account for 69% of the market and 83% of monitor products sold met 

ENERGY STAR performance requirements in 2012 (ENERGY STAR 2012), we estimate that approximately 

55% (=17%/(14%+17%)) of post-2010 LCD-CCFL monitors did not meet ENERGY STAR and 45% did. Then, 

we used 2006-10 LCD-CCFL power draw characteristics to model the power draw of the non-ENERGY 

STAR LCD-CCFLs and data from the ENERGY STAR Displays Product List (2013) for the ENERGY STAR

units. For most ENERGY STAR LCD-CCFL monitors, we used the average LCD-CCFL power draw value from 

the database for each size bin. Since the list had no power measurements for 28- and 29-inch LCD-CCFL 

monitors, we estimated the power draw in that size range using correlations between power draw and 

screen area (see Figure 3-28). 

Although the average screen size of installed monitors in homes increased, which tends to increase 

active-mode power draw, we estimate that post-2010 LCDs draw 22W19 in active mode as compared to

33 W for 2006-2010. This reflects improvements in display technology over that period, most notably 

from LED backlights. Average power draw in sleep and off modes also have decreased since 2010, as the 

ENERGY STAR specification allows a 0.5W maximum power draw for monitors in both modes (EPA 

2013). Table 3-33 shows our power draw estimates by display type and screen size.

 

18 We scaled the total North American unit shipment data (commercial and consumer) by the U.S. population fraction (90%) – based on 35

million people in Canada (Statistics Canada 2013) and 317 million in the U.S. (U.S. Census Bureau 2013) – and by the average consumer fraction 

(38%;Display Search 2011-2013). 

19 We estimated power draw for post-2010 monitors based on a 69% share of the installed base for monitors with LED backlight.

0%

20%

40%

60%

80%

100%

2010 2011 2012 2013

All-in-One Desktop PC Display

Any Backlight

LCD Monitor with LED backlight

LCD Monitor with CCFL backlight
Fraunhofer USA Center for Sustainable Energy Systems 54

Table 3-33: Average power draw estimates for monitors.

Year

Screen 

Size

% of 

installed 

base

Units Power [W]

[inches] [millions] Active Sleep Off

LCD 2010-2013 15-19 35% 9.5 15 0.4 0.3

2010-2013 20-21 29% 7.8 22 0.4 0.3

2010-2013 22-24 33% 8.9 26 0.5 0.3

2010-2013 25-29 4% 1.1 38*0.7

*

0.4

*

2010-2013 30-34 0.2% 0.1 72 0.7 0.6

Subtotal/Wt. Avg. 20.9 28% 27.5 22 0.4 0.3

LCD 2006-2010 19.1 55% 53.5 33 0.9 0.6

LCD Wt. Avg. 20.9 83% 81 30 0.8 0.5

CRT Wt. Avg. 17 17% 16 61 2.0 1.0

Total/Avg. - 17.7 100% 97 34 0.9 0.6

* Values have higher uncertainty than other values in table.

Figure 3-28: Active-mode power draw measurements for ENERGY STAR LCD monitors by backlight technology (EPA 2013).

3.7.1.2.2 Usage

Although we did not ask about monitor usage in the current study we did adjust the usage estimates 

from our prior study according to the computer usage estimates developed from the 2013 CE Usage 

Survey (see discussion below). This showed a decrease in active usage of external monitors in 2013 (see 

Table 3-34). The time an external monitor spends in sleep mode is very similar to the findings of an LBNL 

field-monitoring study20 (LBNL 2013). Furthermore, the time in off mode in 2013 is similar to our 2010 

study, mainly because we assumed that the same percentage of monitors are manually switched off in 

2010 and 2013 (Desktop: 36%, Portable: 40%; FhCSE 2011).

 

20 LBNL (2013) measured 23 monitors using Watts Up? And Kill-A-Watt power meters for between three and ten (or more) 

weeks. It divided the time spent in each mode into High Power, Low Power and Off. Hours were assigned to Off mode if the 

power meter reported 0 W power draw. This assumption may create errors in dividing time between off and sleep modes, 

because most monitors draw more than 0W in off mode, in which case those hours were attributed to sleep mode. Because 

active-mode power draw dominates monitor energy consumption, this effect has a very small impact on monitor UEC.

PLED = 0.0342x2 + 0.096x + 0.5

R2 = 0.50

PCCFL= 0.122x2- 1.57x + 1.5

R2 = 0.72

0

50

100

150

10 12 14 16 18 20 22 24 26 28 30 32 34

Screen Size [inches]

LED backlight CCFL backlight

W
Fraunhofer USA Center for Sustainable Energy Systems 55

Table 3-34: Daily usage of monitors by mode.

Year Monitor Usage [h/day] Source Active Sleep Off

2013 4.2 12.2 7.7 Current study

2013 6.6 12.4 5 LBNL 2013

2010 6.9 9.7 7.4 FhCSE 2011

The main reason for decrease in the active usage of monitors in 2013 is that we changed some aspects 

of the monitor usage model. In the current model, active-mode usage equals the sum of computer 

active usage and computer time in short idle mode, with the time to auto-screen off assumed to be 15 

minutes in 2013 and 20 minutes in 2010. After these 15 minutes the computer monitor turns off 

automatically even if the computer remains on. This yields active-mode usage estimates of 4.7 

hours/day for desktop computers and 3.5 for portable computers (see Computer Sections 3.4.1.2.2 and 

3.5.1.2.2). To estimate monitor usage for the remaining hours (Desktop: 19.3 h/day; Portable: 20.5 

h/day), we first identified the portion of monitors that are always on. This was calculated based on the 

following assumptions, including the computer auto-power management (APM) state (Figure 3-29):

 If a computer has APM enabled, i.e., if a computer is sleeping, hibernating, turned off 

automatically, or has auto-screen off, then the monitor enters either a sleep or off mode.

 If a computer has APM disabled but was manually put into sleep mode or was manually 

switched off, then the monitor is either in sleep or off mode.

 If a computer has APM disabled and was not manually put into sleep mode or manually 

switched off, then the monitor remains on the whole day.

Figure 3-29: Decision diagram for determining monitor operational mode.

Following this methodology, we found a much lower portion of monitors left on for 24 hours a day in 

2010 than 2013, i.e., 3.2%and 1.8% of those associated with desktops and portable computers, 

respectively, as compared to 15% and 10% in 2010. The amount of monitors that were 24 hours on is 

much higher in 2010 compared to 2013 because the 2010 methodology assumed that if a computer 

does not have APM enabled and the monitor was not turned off manually then the monitor is always 
Fraunhofer USA Center for Sustainable Energy Systems 56

on. Based on monitor power-draw measurements in 2013, we changed this so that a monitor associated 

with a computer in sleep or switched off manually is either in sleep or off mode. 

3.7.1.3 Unit and Annual Energy Consumption

Monitor AEC equals 5.7TWh in 2013, with most of the energy consumption occurring in active mode 

(about 5.2TWh). Sleep and off modes account for a very small portion of AEC (0.4 TWh and 0.1 TWh, 

respectively). Table 3-35 shows UEC and AEC breakdowns by display technology and screen size. LCD 

monitors with CCFL backlight technology account for a majority of monitor AEC. 

Table 3-35: UEC and AEC estimates for monitors.

Year Screen Size

[inches]

Units UEC [kWh/yr] AEC

[millions] Active Sleep Off Total [TWh/yr]

LCD 2010-2013 15-19 9.5 23 1.6 0.7 25 0.2

2010-2013 20-21 7.8 34 1.8 0.8 36 0.3

2010-2013 22-24 8.9 40 2.2 0.8 43 0.4

2010-2013 25-29 1.1 58 3.0 1.2 62 0.1

2010-2013 30-34 0.1 110 3.1 1.7 115 <0.05

Subtotal/Wt. Avg. 20.9 27.5 33 1.9 0.8 36 1.0

LCD 2006-2010 19.1 53.5 51 4.0 1.7 56 3.0

LCD Wt. Avg. 19.7 81 46 3 1 51 4.0

CRT Wt. Avg. 17 16 94 8.9 2.8 105 1.7

Total/Avg. - 19.3 97 53 4 2 58 5.7

3.7.2 Comparison with Prior Energy Consumption Estimates

Table 3-36 summarizes prior estimates for residential monitor energy consumption. Our estimated UEC 

(58 kWh/yr) is lower than both FhCSE (2011) and LBNL (2013). Unfortunately, we do not know the 

screen size and technology of monitors metered by LBNL (2013), and therefore cannot readily evaluate 

the difference in UEC. 

Table 3-36: Prior energy consumption estimates for monitors.

Year Units 

[millions]

Power [W] Usage [h/yr] UEC AEC Source Active Sleep Off Active Sleep Off [kWh/yr] [TWh/yr]

2013 97 33 0.9 0.6 1,533 4,453 2,774 58 5.7 Current

2013 - 26 1.0 0.0 2,409 4,526 1,825 67 - LBNL 2013

2010 131 39 1.2 0.9 2,519 3,541 2,701 97 12.7 FhCSE 2011

2010 - 43 1.2 - 1,935 6,825 - 84 - Bensch et al. 2010

2008-CRT - 71 46 3 - - - - - ECOS 2011

2008-LCD - 34 6 0.9 - - - - - ECOS 2011

2006 90 42 1 1 1,865 875 6,020 85 7.6 TIAX 2007

2005 89 45 2 1 1,860 880 6,020 101 9 TIAX 2006

Overall, our AEC estimate in 2013 is 54% lower than in 2010 (FhCSE 2011). Decreases in the installed 

base accounts for the largest portion of this change (51%), followed by decrease in active-mode usage 

(34%), and improvements in the technology (15%). As discussed in the installed base subsection, the 

decrease in the installed base of desktop PCs and an increase in the installed base of all-in-one PCs are 

primarily responsible for the 27% decrease in the installed base of external monitors. The decrease in 

active-mode usage reflects an updated model for both PC and monitor usage that we believe yields 

more accurate usage estimates (see above). 
Fraunhofer USA Center for Sustainable Energy Systems 57

3.7.3 References

CEA. 2014. “2014 CRT Television and Monitors per U.S. Household”. CEA Market Research Report. April.

Cnet. 2010a. ASUS VE276Q 27-inch Review. Oct. http://reviews.cnet.com/lcd-monitors/asusve276q/4507-3174_7-34139489.html

Cnet. 2010b. BenQ M2700HD 27-inch Review. Sep. http://reviews.cnet.com/lcd-monitors/benqm2700hd/4507-3174_7-34069077.html

Dell. 2013. Dell UltraSharp 30 PremierColor Monitor – U3014. Technical specifications. 

http://accessories.us.dell.com/sna/productdetail.aspx?c=us&l=en&cs=04&sku=225-4429

DisplaySearch. 2014. “Quarterly Desktop Monitor Shipment and Forecast Report, 2011-13”

Energie-Atlas Bayern 2.0. Computer, TV & Co. 

http://www.energieatlas.bayern.de/buerger/konsum/computer.html

ENERGY STAR. 2013. Displays Product List. Jun.

ENERGY STAR. 2012. Unit Shipment and Market Penetration Report Calendar Year 2012 Summary. 

http://www.energystar.gov/ia/partners/downloads/unit_shipment_data/2012_USD_Summary_Repo

rt.pdf

ENERGY STAR. 2013. Displays Product List.

http://downloads.energystar.gov/bi/qplist/displays_prod_list.xls. Jun. 

EPA. 2008. Displays Specification. Draft Final Dataset & Analysis. Environmental Protection Agency. Dec. 

http://www.energystar.gov/ia/partners/prod_development/revisions/downloads/monitors/Draft2_

Dataset_Analysis.xls. 

EPA. 2013. ENERGY STAR program requirements for displays. Version 6.0. Environmental Protection 

Agency. Jan. http://www.energystar.gov/products/specs/sites/products/files/ 

Final_Version_6%200_Displays_Program_Requirements.pdf

FhCSE. Urban, Bryan, Kurt Roth, and Verena Tiefenbeck. 2011. “Energy Consumption of Consumer 

Electronics in U.S. Homes in 2010.” Final Report to the Consumer Electronics Association. 

http://www.ce.org/CorporateSite/media/Government-Media/Green/Energy-Consumption-of-CE-inU-S-Homes-in-2010.pdf. Dec.

IDC. 2013. IDC Lowers Forecast Growth for PC Monitors While Average Screen Size Increases. Jun.

http://www.idc.com/getdoc.jsp?containerId=prUS24163113

LBNL. Greenblatt, J. 2013. “Field data collection of miscellaneous electrical loads in Northern California: 

initial results.” Lawrence Berkeley National Laboratory Final Report, LBNL-6115E. Jul.

NPD DisplaySearch. 2012. Quarterly Worldwide FPD Shipment and Forecast Report. http://techcrunch. 

com/2012/10/16/study-average-display-size-climbing-on-all-devices-except-for-mobile-pcs/

SID. Kim, J. and P. Semenza. 2012. How LEDs Have Changed the LCD Industry. Technical Paper. Apr.

Statistics Canada. 2013. “Canada Population Estimates.” http://www.statcan.gc.ca/start-debut-eng.html

TIAX. Roth, K., R. Ponoum, and F. Goldstein. 2006. “U.S. Residential Information Technology Energy 

Consumption in 2005 and 2010.” Final Report by TIAX LLC to the U.S. Department of Energy, Building 

Technology Program. Mar.

TIAX. Roth, K., K. McKenny. 2007. “Energy consumption by consumer electronics in U.S. Residences.” 

Final report to the Consumer Electronics Association (CEA). Jan.

U.S. Census Bureau. 2013. “U.S. Population.” http://www.census.gov/#
Fraunhofer USA Center for Sustainable Energy Systems 58

3.8 Network Equipment

3.8.1 Current Energy Consumption

Residential network equipment can be classified in three categories: (1) broadband modems without 

integrated routers; (2) broadband modems with integrated routers called Integrated Access Devices 

(IADs) or Broadband Gateways; and (3) routers and other devices. Devices from all categories may 

support wired connections, wireless connections (Wi-Fi), or both.

Broadband modems and IADs are collectively known as broadband access devices, and subscribers use 

these to connect to a high-speed Internet service provider (ISP). Our installed base estimates include 

cable, digital subscriber line (DSL) (including asymmetric digital subscriber line (ADSL) and very-high-bitrate digital subscriber line (VDSL)), fiber optic, and satellite modems in the broadband modem and IAD 

categories. Less common modems, including stationary WiMAX, 3G, 4G modems and wireless mobile 

hotspot devices, are included in the routers and other devices category. 

Devices listed in the routers and other category are used to establish a local area network (LAN) for 

communication between household consumer electronics. Routers, the most common and feature-rich 

devices, can manage data transfer between multiple computer networks and can provide security, 

Internet connection sharing, and other advanced features. We did not include switches and hubs in the 

routers and other devices category in 2013 because of their very low initial estimated AEC of 0.01 TWh 

for less than 1 million units.

3.8.1.1 Installed Base

Broadband subscription penetration in 2013 was 75% according to the CE Sales and Forecasts (2013), an 

8% increase from 2010 (FhCSE 2011). This estimate generally agrees with the 70% from another surveybased estimate, PEW (2013). Growth in broadband penetration has slowed since 2010, while in-home

network penetration has grown steadily (see Figure 3-30), i.e., from between 40 and 54 percent of

households in 2010 (FhCSE 2011) to 62% in 2013. Internet access penetration has remained constant at 

78% of households over the past three years (CEA 2013a). 

Figure 3-30: Portion of households with broadband Internet subscriptions and home networks (CEA 2013b).

Among the estimated 207 million network devices installed in 2013, 49 million were modem-only, 64 

IAD, and 94 routers and other (NRDC 2013, LBNL 2010, CEA 2013a; see Table 3-37). In the modem 

58 61

69 70 74 75

30 34

40

48 54

62

0%

20%

40%

60%

80%

100%

2008 2009 2010 2011 2012 2013

broadband internet subscriptions

network penetration
Fraunhofer USA Center for Sustainable Energy Systems 59

category, the installed base of cable modems decreased by 49% from 2010, whereas the installed base 

of DSL modems increased by 11%. The installed base of fiber and satellite modem installed base 

increased three-fold and nine-fold, respectively. We estimate that the installed base of cable IADs 

tripled from 2010 to 2013, while there are 13% fewer DSL IAD devices in 2013 than in 2010.

Of the network equipment studied in less detail, mobile wireless hotspots underwent the largest growth 

in household penetration from 2011, reaching 21% in 2013. The installed base of wireless mobile 

hotspots together with 3G and 4G modems totaled 35 million devices in 2013 (CEA 2013a).The installed 

base of wireless routers comes from NRDC (2013), a 15% increase from 2010. Finally, we estimate that 

the installed base of WiMAX devices remains low (approximately 2% of households21). 

Table 3-37: Installed base of network devices (LBNL 2010, CEA 2013a, NRDC 2013).

Installed Base [millions] Category

2010 2011 2012 2013*[%]

Modem-only

Cable modem 35 32 27 18 37%

DSL modem 5.4 4 4 6 12%

Fiber optic terminal (all) 5.4 7 10 16 33%

Satellite modem 1.0 - - 9 18%

Subtotal/Wt. Avg. 46 - - 49 100%

IAD (Modem + Router)

Cable IAD 12 17 27 37 58%

DSL IAD 31 35 37 27 42%

Subtotal/Wt. Avg. 42 - - 64 100%

Router and Other

Wireless router 46 45 42 53 56%

Wired-only router/other 1.7 - - 1.7 2%

WiMAX 1 - - 2.4 3%

Access point†- - - 2 2%

Wireless mobile hotspot‡- - - 35 37%

Subtotal/Wt. Avg. 49§- - 94 100%

Total/ Weighted Avg. 139 - - 207 -

* Adjusted based on projections from LBNL (2010) and internet subscriptions (CEA 2013a).

† Hardy et al. (2013) defines an access point as “a device that provides Institute of Electrical and 

Electronics Engineers (IEEE) 802.11 (Wi-Fi) connectivity to multiple clients as its primary function. An 

access point ...extends the range of a wireless signal but does not assign IP addresses to networked 

devices and therefore cannot be used to connect multiple edge devices in the absence of a wired or 

wireless router.”

‡ This category includes 3G and 4G CPE and wireless mobile hotspots devices.

§ Fraunhofer (2011) did not include wireless mobile hotspot devices in the installed base; their 

penetration started to grow rapidly in 2011.

The installed base estimates for network equipment in Table 3-37 show a higher penetration of network 

equipment for cable than for DSL or fiber-optic. This agrees with the results from a recent CEA survey 

(CEA 2013a) shown in Figure 3-31 (left). Our estimates of installed base of routers indicate that 96% had 

wireless functionality. According to the CEA ownership survey (CEA 2013a), 51% of households had a 

wireless connection at their homes in 2013.

 

21 Assuming that 2% of US households who answered “some other way” on the question “What type of Internet service do you have at home?” 

in CEA Ownership Survey (2013a) have WiMAX internet service.
Fraunhofer USA Center for Sustainable Energy Systems 60

Figure 3-31: Type of Internet service at home (CEA 2013a).

3.8.1.2 Unit Energy Consumption

3.8.1.2.1 Power Draw

Our evaluation of the power draw of network equipment is based upon the ENERGY STAR dataset of 

measurements for 198 small network equipment devices (EPA 2013b) and measurements from 

laboratory testing and in-home monitoring using the ENERGY STAR test procedures (NRDC 2013, Hardy 

et al. 2013). Together, these studies provided a larger measurements data set than we used in the 2010 

study. Generally, the active power draw measurements for cable and DSL network equipment by NRDC 

(2013) and EPA (2013b) are higher than the FhCSE (2011) estimates for 2010. For fiber optic terminals 

(ONTs), we relied on EPA measurements of 19 ONTs that draw, on average, 6.7 W. To evaluate the 

active power draw of wired routers, we took the average power draw of 19 wired routers measured by 

ECCJ (2008).22 Active power draws for wireless routers and access points we took as average power of 

measured devices by EPA (wireless routers: n=50, access point: n=13). We could not find new 

measurements for satellite modems, WiMAX network equipment and wireless mobile hotspot devices in 

2013; therefore we used the active power draw values from our previous study (FhCSE 2011) and values 

from manufacturers’ specifications (Motorola 2013, Greenpacket 2013, Fritzbox 2013, CMAX 2013). 

Standby power draw estimates are based on values from the previous Fraunhofer CSE study (FhCSE 

2011) because neither NRDC nor EPA measured power draw in standby mode. We assumed that 

standby power draws have not changed appreciable since 2010. In practice, the standby mode has a 

small impact on network equipment UEC since these devices spend most of the time in on mode. Table 

3-38 presents active mode and standby mode power draw values. 

The first ENERGY STAR specification for small network equipment took effect in Sept. 2013. Thus, this 

may have shaped the energy consumption characteristics of network equipment sold right before the 

point in time for this analysis (i.e., mid-2013) (EPA 2013a).

 

22 We were unable to find shipment data for wired routers between 2010. We expect, however, that the installed base of wired routers has not 

changed from 2010 due to growing wireless connections in US homes. Therefore, power draws estimates from ECCJ (2008) represent most of 

the installed base.

Cable

43%

DSL

26%

Fiber

14%

Satellite

8%

Dial-up

7%

Other

2%
Fraunhofer USA Center for Sustainable Energy Systems 61

Table 3-38: Power draws for network equipment (NRDC 2013, EPA 2013b)

Devices Overall Power [W]

[millions] [%] Active Standby

Modem-only

Cable modem 18 9% 6.7 0.1

DSL modem 6 3% 5.4 0.1

Fiber optic terminal (all) 16 8% 6.7*0.1

Satellite modem 9 4% 9.5 0.1

Subtotal/Wt. Avg. 49 24% 7.1 0.1

IAD (Modem + Router)

Cable IAD 37 18% 8.0 1.5

DSL IAD 27 13% 7.3 1.5

Subtotal/Wt. Avg. 64 31% 7.7 1.5

Router and Other

Wireless router 53 26% 7.5 1.8

Wired-only router / other 1.7 <1% 6.7 0.0

WiMAX 2.4 1% 12†0.0‡

Access point 2 1% 5.5 0.0‡

Wireless mobile hotspot 

devices

35 17% 7.0†0.0‡

Subtotal/Wt. Avg. 94 45% 7.4 1.0

Total/ Weighted Average 207 100% 7.4 0.9

* The active power draw of a fiber optic terminal varies significantly and depends on the data 

transmitting by device. Some in-home fiber network equipment also provides TV contents in 

addition to internet and phone service (NRDC 2013).

† These values have a high uncertainty.

‡ We were unable to find these data.

3.8.1.2.2 Usage

Field monitoring studies indicate that broadband Internet modems and network devices are normally 

always on and ready to use, and most units automatically turn and remain on when plugged in. The 

2010 CE Usage Survey found that 12% of U.S. adults reported that their modems were switched off 

when not in use, 86% reported always on, and 2% didn’t know. Thus, we estimate that an average

modem is on 21.4 hours per day, or 7,826 hours per year and turned off the remaining hours (FhCSE 

2011). We assume that the time spend in active mode has not changed significantly from 2010 and did 

not perform an updated usage survey for small network equipment. In the case of wireless mobile 

hotspot devices, this almost certainly overestimated their active-mode usage.

3.8.1.3 Unit and Annual Energy Consumption

We estimate that network equipment consumed 12 TWh in 2013: 2.7 TWh from modems, 3.9 TWh from 

IADs, and 5.5 TWh from routers and other (see Table 3-39). In 2013, cable, satellite modems and fiber 

optic terminals consumed the largest portion of modem energy consumption. Among IAD devices, cable 

modems with integrated routers consumed more energy than DSL IADs due to a higher installed base. 

Wireless routers accounted for a majority (58%) of router and other energy consumption due to their 

high penetration, with increasingly common wireless mobile hotspot devices accounting for much of the 

remaining energy in this category (see Figure 3-32). 
Fraunhofer USA Center for Sustainable Energy Systems 62

Table 3-39: UEC and AEC calculations for network equipment.

Devices Overall UEC [kWh/yr] AEC

[millions] [%] Active Standby Total [TWh/yr]

Modem-only

Cable modem 18 9% 52 0.1 53 0.9

DSL modem 6 3% 42 0.1 42 0.3

Fiber optic terminal (all) 16 8% 52 0.1 53 0.8

Satellite modem 9 4% 74 0.1 74 0.7

Subtotal/Wt. Avg. 49 24% 55 0.1 55 2.7

IAD (Modem + Router)

Cable IAD 37 18% 63 1.4 64 2.4

DSL IAD 27 13% 57 1.4 59 1.6

Subtotal/Wt. Avg. 64 31% 60 1.4 62 3.9

Router and Other

Wireless router 53 26% 59 1.7 60 3.2

Wired-only router / other 1.7 <1% 52 0.0 52 0.1

WiMAX 2.4 1% 94 0.0 94 0.2

Access point 2 1% 43 0.0 43 0.1

Wireless mobile hotspot devices 35 17% 55 0.0 55 1.9

Subtotal/Wt. Avg. 94 45% 58 0.9 59 5.5

Total/Weighted Average 209 100% 58 0.9 58 12

Figure 3-32: AEC for small network equipment.

3.8.2 Comparison with Prior Energy Consumption Estimates

Table 3-40 and Table 3-41 summarize prior estimates for broadband modems and network device

energy consumption. Our current estimates are higher than our previous study (FhCSE 2011), primarily 

due to significant growth in the installed base of fiber optic terminals, wireless routers and wireless 

mobile hotspot devices. 

0 0.5 1 1.5 2 2.5 3 3.5

Cable modem

DSL modem

Fiber modem (all)

Satellite modem

Cable IAD

DSL IAD

Wireless router

Wired-only router / other

Hub or switch

Access point

Wireless mobile hotspot (LTE)

WiMAX

Modem-only IAD Router and Other

AEC [TWh]
Fraunhofer USA Center for Sustainable Energy Systems 63

Table 3-40: Prior energy consumption estimates for broadband access devices (modems and IADs)

Units Power [W] Usage [h/yr] UEC AEC

Year [millions] Active Standby Active Standby [kWh/yr] [TWh/yr] Source

2013 113 7.4 0.9 7,826 934 59 6.7 Current

2012 88 7.5 - 8,760 0 65 5.7 NRDC 2013

2010 88 6.1 0.8 7,826 934 48 4.3 FhCSE 2011

2010 87 6.0 - 8,760 0 53 4.6 LBNL 2010

2008 71 5.8 - 8,760 0 51 3.6 LBNL 2010

2006 46 6.0 - 8,760 0 53 2.4 TIAX 2007

2005 32 6.0 - 8,760 0 53 2.6 TIAX 2006

Table 3-41: Prior energy consumption estimates for routers and other devices (non-modem)

Units Power [W] Usage [h/yr] UEC AEC

Year [millions] Active Standby Active Standby [kWh/yr] [TWh/yr] Source

2013 57 7.4 1.0 7,826 934 57 3.4*Current

2012 56 5.5 - 8,760 0 48 2.8 NRDC 2013

2010 49 5.4 1.7 7,826 934 44 2.1 FhCSE 2011

2010 50 5.5 - 8,760 0 48 2.4 LBNL 2010

2008 45 5.5 - 8,760 0 48 2.2 LBNL 2010

2005 15 6.0 - 8,760 0 53 0.8 TIAX 2006

* AEC does not include wireless mobile hotspot devices and WiMAX modems, but does include hubs and switches 

(not shown in prior tables).

Figure 3-33: U.S. broadband household subscribers by technology type (LBNL 2010, TIA 2013, CEA 2013a).

3.8.3 References

CEA. 2013a. “15th Annual CE Ownership and Market Potential Study.” CEA Market Research Report, 

April, 2013. Consumer Electronics Association.

CEA. 2013b. “U.S. Consumer Electronics Sales & Forecasts 2009-2014.” CEA Market Research Report, 

July, 2013. Consumer Electronics Association.

Cisco. 2011.” IEEE 802.3az Energy Efficient Ethernet: Build Greener Networks.” White paper. 

http://www.cisco.com/en/US/prod/collateral/switches/ps5718/ps4324/white_paper_c11-

676336.pdf

CMAX. 2013. Technical specifications CMC-100Li. http://www.cmaxwireless.co.kr/pro0104.html?part=4

DisplaySearch. 2014. “Quarterly Desktop Monitor Shipment and Forecast Report, 2011-13”

ECCJ. “Small Routers & L2 Switches.” Final report. The Energy Conservation Center Japan. Apr. 2008 

https://www.eccj.or.jp/top_runner/pdf/tr_small_routers-apr_2008.pdf

EPA. 2013a. ENERGY STAR program requirements for Small Network Equipment. Version 1.0. 

Environmental Protection Agency. Nov. 

0%

20%

40%

60%

80%

100%

2008 2009 2010 2011 2012 2013 2014 2015 2016

Satellite

WiMAX

FTTH

Cable

DSL
Fraunhofer USA Center for Sustainable Energy Systems 64

http://www.energystar.gov/products/specs/sites/products/files/SmallNetworkEquipment_V1_ENER

GYSTAR_ProgramRequirements_Nov2013_0.pdf

EPA. 2013b. “SNE Version1.0 Draft 3 Dataset.”

FhCSE. Urban, Bryan, Kurt Roth, and Verena Tiefenbeck. 2011. “Energy Consumption of Consumer 

Electronics in U.S. Homes in 2010.” Final Report to the Consumer Electronics Association. 

http://www.ce.org/CorporateSite/media/Government-Media/Green/Energy-Consumption-of-CE-inU-S-Homes-in-2010.pdf. Dec.

Fritzbox. 2013. Product description Fritz box 6810. http://www.4gltemall.com/fritz-box-6810-ltecpe.html

Greenpacket. 2013. Technical specifications EX 250. 

http://www.digicel4gbroadband.com/assets/uploads/WiMAX_CPE_Standard_Modem_____EX_250_

Technical_Spec.pdf

Hardy, G., D. Denkenberger, J. Swofford, S. Foster Porter, A. Pawashe, K. Dayem, and D. Driscoll. 2013. 

“Analysis of Standards Proposal for Small Network Equipment”. Codes and Standards Enhancement 

(CASE) Initiative for PY 2013: Title 20 Standards Development. Ecova. Jul.

http://www.energy.ca.gov/appliances/2013rulemaking/documents/proposals/12-AAER2A_Consumer_Electronics/California_IOUs_Response_to_the_Invitation_for_Standards_Proposals_f

or_Small_Network_Equipment_2013-07-29_TN-71761.pdf 

LBNL. Lanzisera, S. and Nordman, B. 2010. EEDN Task 2.2.3: Network equipment scoping report. 

Lawrence Berkeley National Laboratory. Mar. 

LBNL. Meier, A., Nordman, B., Busch, J., and Payne, C. 2008. “Low-power mode energy consumption in 

California homes.” CEC-500-2008-035. Lawrence Berkeley National Laboratory. Sept. 

http://www.energy.ca.gov/2008publications/CEC-500-2008-035/CEC-500-2008-035.PDF. 

Motorola. 2013. Datasheet for Motorola CPE i800. 

http://www.motorolasolutions.com/web/Business/Product%20Lines/Motowi4/CPEi_800/Images/Sta

ticFiles/CPEi_800_DataSheet.pdf

NRDC. 2013. “Small Network Equipment Energy Consumption in U.S. Homes.” NRDC Issue Paper. Jun.

http://www.nrdc.org/energy/files/residential-network-IP.pdf

Pew. Zickuhr,K., A. Smith. 2013. “Home Broadband 2013.” Aug.

http://pewinternet.org/Reports/2013/Broadband/Findings.aspx

Statistics Canada. 2013. “Canada Population Estimates.” http://www.statcan.gc.ca/start-debut-eng.html

U.S. Census Bureau. 2013. “U.S. Population.” http://www.census.gov/#

TIA. 2013. “Market Review and Forecast.” Mar.

TIAX. Roth, K., R. Ponoum, and F. Goldstein. 2006. “U.S. Residential Information Technology Energy 

Consumption in 2005 and 2010.” Final Report by TIAX LLC to the U.S. Department of Energy, Building 

Technology Program. Mar.

TIAX. Roth, K., K. McKenny. 2007. “Energy consumption by consumer electronics in U.S. Residences.” 

Final report to the Consumer Electronics Association (CEA). Jan. 
Fraunhofer USA Center for Sustainable Energy Systems 65

3.9 Smart Phones

Smartphones are mobile phones with Internet connectivity. They include phones with operating systems 

running iOS, Android, Windows Mobile and BlackBerry. 

3.9.1 Current Energy Consumption

3.9.1.1 Installed Base

We estimate an installed base of 166 million smartphones that have been used in the past month (Nov. 

2013). Some U.S. adults indicated that their households owned smartphones, but that they personally 

did not use any. Given the nascence of smartphones, as a lower bound, we assume that such 

households have one smartphones which is used by others. Our estimate from late 2013 is higher than 

the estimate from early 2013 by CEA (2013a), due to the high sales volume of smartphones in 2013 

(estimated 127 million by CEA 2013b). Our installed base is consistent with other recent estimates (see 

Table 3-42).

Table 3-42: Installed base estimates for smartphones from different data sources.

Data Date Household 

penetration

Households

[millions]

Units / owner 

household

Installed Base 

[millions] Source

Dec 2013 66% 79 2.1 166*CE Usage Survey

Feb 2013 58% 69 2.2 152 CEA 2013a

Jun 2013 - - - 164† Magid 2013

Jun 2013 - - - 151‡Pew 2013b

Q2 2013 - - - 142§Nielsen 2013a

* Sum of our estimates for smartphones which U.S. adults personally used (152 million) and smartphones which are owned in their 

households, but not personally used by the U.S. adult, assuming one for each of those households (14 million).

† Lower bound estimate based on 61% of U.S. population (ages 8-65), 316.1 million U.S. population in 2013 (U.S. Census 2013), 85% of U.S. 

adults use the Internet (Pew 2013).

‡ Lower bound estimate based on 56% of U.S. adults.

§ Lower bound estimate based on 53% of U.S. online users aged 13+.

Figure 3-34: Distribution of households with smartphones used during the past month (Nov. 2013) vs. Ownership (Feb. 2013, 

CEA 2013).

Unlike for tablets, we asked only about the (primary) smartphones most used by the U.S. adult, since 

they are personal devices; respondents are unlikely to know how other smartphones are used in the 

household.

34%

47%

9.8%

4.0% 5.1%

0%

10%

20%

30%

40%

50%

0 1 2 3 ≥4

% of U.S. Households
Fraunhofer USA Center for Sustainable Energy Systems 66

Table 3-43: Plugged-In installed base estimates for smartphones from the CE Usage Survey.

Households [millions]

Smartphones Used per Owner Household 

Device Not Owned 1 2 3 ≥4

Smartphones 40 42 12 4.8 6.1

3.9.1.2 Usage

We estimate that smartphones are used for 4.1 hours/day on average (Median=2.0 hours/day). Our 

median estimate is similar to other estimates of 2.6 hours for smartphones by DOE (2012) and the 

measured average of 2.6 hours/day for smartphones or tablets by Flurry Analytics (2013). However, our 

estimate is higher than that of Experian (2013) of 58 minutes/day. Experian (2012) also found phone 

usage to vary with phone type, e.g., iPhones are used more than Android smartphones (1.25 vs. 0.82 

hours/day).

3.9.1.3 Energy Consumption

We use the same energy model to evaluate smart phone energy consumption as we did for tablets (see 

Section 3.10.1.2). The model considers energy consumption due to battery charging, including the 

impact of charger inefficiency and power draw when the smartphone is idle or unplugged from the 

charger but the charger remains plugged into the wall. Appendix B.2 presents additional details. We 

measured power draws by metering 5 smartphone units with Watts Up? .Net and Yokogawa WT210 

power meters. Based on survey responses, we estimate that original chargers are used 82% of the time, 

and other chargers 18% of the time.

Table 3-44: Representative battery capacity for smartphones, and power draw estimates for original and other chargers.

Charger Type Relative 

Usage Time

Battery Capacity 

[Wh]

Charger Efficiency 

[%]

Power Draw [W]

Idle Unplugged

Original 82% 6.5 76% 0.49 0.13

Others 18% - 67% 0.55 0.19

Weighted Average - 6.5 74% 0.50 0.14

3.9.1.3.1 Charging

We calculate the energy consumption due to charging smartphones by multiplying the number of times 

the battery is charged in a day by the average increase in battery level (from pre-charging to postcharging) for each charge session, and the additional energy consumed due to charger inefficiency (see 

Table 3-45). Our estimate of 0.92 charge cycles/day is similar to the estimate by DOE (2012) of 0.80 

charges cycles/day and the assumption by OPower (2012) of one charge cycle/day. 

Table 3-45: Energy consumption estimates due to charging smartphones.

Device 

Battery Level Number Per Day Battery 

Capacity 

[Wh]

Charger 

Efficiency 

[%]

Energy Consumption

PreChargePostChargeCharge 

Sessions

Charge 

Cycles

Full Charge 

[Wh]

Per Day 

[Wh/day]

Smartphone 29% 95% 1.5 0.92 6.54 76% 8.8 7.7

3.9.1.3.2 Idle

We calculate the energy consumption in idle mode by multiplying the remaining time plugged in after 

charging to partial battery capacity in one day by the power draw while idle. As for tablets, for simplicity 
Fraunhofer USA Center for Sustainable Energy Systems 67

we average the charging rates for <90% and ≥90% battery levels to estimate the average time for a full 

charge, and assume a linear relationship for the time to partial charging. Based on survey responses, we 

estimate that 64% of smartphones are charged only with the original charger and 11% are charged only

with other chargers, and the remaining 25% of smartphones are charged with both the original and 

other chargers. DOE (2012) estimated higher time and power draw in idle mode, that yield a higher

energy consumption estimate (3.6 vs. 2.5 Wh/day).

Table 3-46: Energy consumption estimates due to smartphones being plugged into chargers after being fully charged (idle).

Device 

Time [hr/day]

Power Draw 

Idle Mode 

[W]

Energy 

Consumption 

[Wh/day]

Connected to Charger Charging

Original Idle

Charger Others All Chargers Full Charge [hr]

Per Day 

[hr/day]

Smartphone 4.1 1.0 5.2 2.1 1.9 3.3 0.50 2.5

(DOE 2012) - - 7.2 - 2.6 4.6 0.78 3.6

3.9.1.3.3 Unplugged

We estimate that on average smartphone chargers plugged into the wall socket for 15 hours/day, but 

49% of users leave them plugged in all the time (24 hours/day). Averaged over all smartphones, 

including those that do not use another charger, “other” smartphone chargers are plugged into the wall 

socket for 6 hours/day. Therefore, for smartphones in the unplugged mode, the total energy 

consumption of their chargers is 3.6 Wh/day. DOE (2012) estimated that users leave their smartphones 

plugged in for a shorter amount of time, and therefore have a higher unplugged time (6.6 vs. 11 

hours/day). The DOE (2012) energy consumption is about half our estimate for the original charger (0.7 

vs. 1.3 Wh/day).

Table 3-47: Energy consumption estimate for smartphones in unplugged mode.

Charger Type

Time [hr/day]

Power Draw 

[W]

Energy 

Consumption 

[Wh/day]

Charger Plugged 

Into Wall

Device 

Unplugged

Original Charger 15 11 0.13 1.3

Others*6.0 4.4 0.18 0.8

All Chargers - - - 2.2

(DOE 2012) 14 6.6 0.11 0.7

* Since we did not ask about other chargers, we assume that if other chargers are used (>0 

hours/day), then they are left plugged in the same amount of time as the original charger. Note that 

mean estimates include responses indicating no use of other chargers (0 hours/day).

3.9.1.4 Unit and Annual Energy Consumption (UEC and AEC)

Our calculations yield an average smartphone UEC of 4.5 kWh/year and an AEC of 0.75 TWh/year. Our 

estimates show that non-charging modes account for about one-third of energy consumption (see 

Figure 3-35). Although the UEC of smartphones is 74% of that of tablets (see Section 3.10), smartphones 

have a 66% greater installed base, resulting in a somewhat (24%) higher AEC.
Fraunhofer USA Center for Sustainable Energy Systems 68

Figure 3-35: Energy consumption of smartphones in different operational modes.

Table 3-48: UEC and AEC values for smartphones.

Type Energy Consumption

[Wh/day]

UEC [kWh/year] Installed Base

[millions]

AEC

Charging Idle Unplugged Total [TWh/yr]

iPhones 12 2.4 1.0 1.0 4.3 70*0.30

Android Samsung 13 3.7 0.8 0.4 4.9 22*0.11

All Smartphones 12 2.8 0.9 0.8 4.5 166 0.75

* Installed base for various iPhone and Android Samsung smartphone models estimated by representative weights of selected most 

popular smartphones scaled to the total installed base of smartphones. Note that this does not sum to the estimate for total installed 

base, since there are other smartphone models.

3.9.2 Comparison with Prior Energy Consumption Estimates

Our UEC estimates for smartphones are similar to those of other sources (see Table 3-49). Our estimates 

verify commonly held assumptions that smartphones are charged about once a day. OPower (2012) 

estimated slightly higher energy consumption for charging (indicating lower efficiencies compared to 

manufacturer specifications and product reviews, i.e., 57% for iPhone 5 and 65% for Samsung Galaxy 

S3). However, we account for additional modes that consume additional energy, specifically the idle and 

unplugged modes. 

Table 3-49: Current and prior energy consumption estimates for smartphones.

Year

Units*

[millions]

UEC [kWh/yr] AEC

[TWh/yr] Device Model Source

Charging Idle Unplugged Total

2013 166 2.8 0.9 0.8 4.5 0.75 All smartphones Current

2013 26 2.4 1.3 1.1 4.8 0.12 iPhone 5 Current

2013 14 2.3 0.7 1.1 4.0 0.06 iPhone 4 Current

2013 13 3.4 0.8 0.4 4.5 0.06 Samsung Galaxy S3 Current

2012

2012

170†3.5 0 0 3.5 0.59†iPhone 5 OPower 2012

- 4.5 0 0 4.5 - Samsung Galaxy S3 OPower 2012

2012

2012

- - - - 3.3 - iPhone 4 EPRI 2012

- - - - 2.2 - iPhone 3G EPRI 2012

2012 - 5.3‡- 0.3 5.5 - Smartphones DOE 2012

* Installed base for select smartphones estimated by aggregated usage share and total installed base of smartphones.

† Based on projected global sales in 2012.

‡ Combined UEC for charging and idle.

3.9.3 References

CEA. 2010. “12th Annual household CE Ownership and Market Potential.” CEA Market Research Report. 

Consumer Electronics Association. May, 2010. Consumer Electronics Association.

CEA. 2013a. “15th Annual CE Ownership and Market Potential Study.” CEA Market Research Report, 

April, 2013. Consumer Electronics Association.

0

5

10

15

Any

smartphone iPhones AndroidSamsung

Unplugged 2.2 2.7 1.0

Idle 2.5 2.7 2.2

Charging 7.7 6 10

Total 12 12 13

Wh/d
Fraunhofer USA Center for Sustainable Energy Systems 69

CEA. 2013b. “U.S. Consumer Electronics Sales & Forecasts 2009-2014.” CEA Market Research Report, 

July, 2013. Consumer Electronics Association.

CEA. 2013c. Steve Koenig. Private correspondence, Nov. 2013. Consumer Electronics Association.

CEA. 2014. “Consumer Outlook on Tablets – Jan. 2014 Edition.” Jan. 2014.

DOE. 2012. “Rulemaking for Battery Chargers and External Power Supplies Energy Conservation 

Standard. Energy Use Analysis Spreadsheet.” Feb. 17, 2012.

http://www.regulations.gov/#!documentDetail;D=EERE-2008-BT-STD-0005-0084. Retrieved Feb. 6, 

2014.

EPRI. 2012. “iPad Electricity Consumption in Relation to Other Energy Consuming Devices - Executive 

Summary.” Jun. 21, 2013. http://www.epri.com/OurWork/Documents/Energy%20Efficiency/iPadEnergyConsumeExecSummary6-2012Final.pdf. Retrieved 

Sept. 20, 2013.

Experian. 2013. Fetto, J. “Americans spend 58 minutes a day on their smartphones” May 28, 2013. 

http://www.experian.com/blogs/marketing-forward/2013/05/28/americans-spend-58-minutes-aday-on-their-smartphones/. Retrieved Oct. 24, 2013.

Flurry Analytics. 2013. Khalaf, S. “Flurry Five-Year Report: It’s an App World. The Web Just Lives in It.” 

Apr. 3, 2013. http://blog.flurry.com/bid/95723/Flurry-Five-Year-Report-It-s-an-App-World-The-WebJust-Lives-in-It. Retrieved Nov. 12, 2013.

Magid. 2013. “Tablets Find a Home in More U.S. Homes.” Jun. 9, 2013. 

http://www.magid.com/node/250. Retrieved Sept. 20, 2013.

Nielsen. 2013. “The Mobile User.” Feb. 25, 2013. http://www.nielseninsights.it/wpcontent/uploads/2013/03/03.-global_mobile_report_02_25.pdf. Retrieved Aug. 6, 2013.

NPD. 2013. “Internet Connected Devices Surpass Half a Billion in U.S. Homes, According to The NPD 

Group.” Mar. 18, 2013. https://www.npd.com/wps/portal/npd/us/news/press-releases/internetconnected-devices-surpass-half-a-billion-in-u-s-homes-according-to-the-npd-group/. Retrieved Jan. 

24, 2014.

OPower. 2012. Fischer, B. “How much does it cost to charge an iPhone 5?” Sept. 27, 2012. 

http://blog.opower.com/2012/09/how-much-does-it-cost-to-charge-an-iphone-5-a-thoughtprovokingly-modest-0-41year. Retrieved Oct. 17, 2013.

Pew. 2013b. Smith, A. “Smartphone Ownership 2013.” Jun. 5, 2013. 

http://pewinternet.org/Reports/2013/Smartphone-Ownership-2013/Findings.aspx. Retrieved Oct. 

17, 2013.
Fraunhofer USA Center for Sustainable Energy Systems 70

3.10 Tablet Computers

Tablets include the iPad, Android tablets, and Windows 8 tablets, but exclude notebook or ultraportable PCs with touch screens. While individually these devices do not consume much energy, 

collectively their energy consumption is notable due to a large and rapidly growing install base.

3.10.1 Current Energy Consumption

3.10.1.1 Installed Base

We estimate an installed base of 100 million tablets that have been used in the past month. Some U.S. 

adults indicated that their households owned tablets, but that they personally did not use any. Given the 

relatively recent market entry of tablets, as a lower bound, we assume that such households have one 

tablet which is used by others. Our estimate from late 2013 exceeds that from early 2013 by CEA 

(2013a), due to the high sales volume of tablets in 2013 (estimated at 113 million by CEA 2013b). Our 

installed base agrees with other recent estimates (see Table 3-50).

Table 3-50: Recent installed base estimates for tablets.

Data Date Household 

penetration

Households

[millions]

Units / owner 

household

Installed Base 

[millions] Source

Dec 2013 57% 67 1.47 100*CE Usage Survey

Feb 2013 39% 46 1.50 70 CEA 2013a

Jul 2013 - 41†- - Parks Associates 2013

Jun 2013 - - - 118†† Magid 2013

Jun 2013 - - - 91§Pew 2013b

Q1 2013 - 49 - - NPD 2013

2013 100 Representative

* Sum of our estimates for tablets that U.S. adults personally used (73 million) and tablets owned by their households but not personally 

used by the respondent, assuming one for each of those households (26 million).

† Lower bound estimate based on 48% of U.S. broadband households, 119 million U.S. households in 2011 (U.S. Census 2011), 72% of U.S. 

Internet household penetration in 2011 (U.S. Census 2011).

†† Lower bound estimate based on 44% of U.S. online population (ages 8-65), 316.1 million U.S. population in 2013 (U.S. Census 2013), 85% of 

U.S. adults use the Internet (Pew 2013).

‡ Lower bound estimate based on 57% of U.S. online households indicating they own at least one tablet.

§ Lower bound estimate based on 35% of U.S. adults indicating they own at least one tablet, 75.6% adults in U.S. population in 2012 (U.S. 

Census 2012), 313.9 million U.S. population in 2012 (U.S. Census 2012).

Figure 3-36: Percentage of households with tablets used during the past month (Nov. 2013) vs. Ownership (Feb. 2013) (CEA 

2013).

Similar to portable PCs, we asked about the most used (primary) tablet and second most used 

(secondary) tablets. 

43%

47%

6.2%

1.8% 1.9%

0%

10%

20%

30%

40%

50%

0 1 2 3 ≥4

% of U.S. 

Households
Fraunhofer USA Center for Sustainable Energy Systems 71

Table 3-51: Plugged-In installed base estimates for tablets from the CE Usage Survey.

Device Type

# Used [million households] Usage Base [million units]

1

*

2 3 ≥4 All Primary Second+

Tablets 56 7.3 2.2 2.3 100 68 32

* We include estimates where the U.S. adult indicated using 0 tablets, but whose household owns >0 tablets.

Primary: number of primary, i.e., most-used, tablets.

Second+: number of tablets that are not primary, i.e., secondary, tertiary, etc.; treated as secondary in energy model.

3.10.1.2 Usage

We asked respondents how long their tablets were used yesterday. We estimate that tablets are used 

2.5 hours a day on average (Median=1.5 hours). Our mean estimate is similar to the measured average 

of 2.6 hours for smartphones or tablets by Flurry Analytics (2013).

3.10.1.3 Energy Consumption

Mobile devices are typically used while running on their batteries. Using the energy usage model 

described in Appendix B.2, we calculate the energy consumption for their usage by estimating the 

energy consumed to charge their batteries. Their battery chargers (BC) also consume energy while 

plugged into the wall outlets. Therefore, we consider the energy consumption due to charging and the 

charger in the following modes:

 Charging: When recharging the battery of the mobile device to its full capacity with an 

additional energy loss due to charging inefficiencies. DOE’s battery charger rulemaking refers to 

this mode as “active.”

 Idle: When the mobile device screen is off and the device is connected to its charger but not 

charging. The power draw in this mode is higher than the power draw on the battery when the 

mobile device is running on its battery and disconnected from the charger. DOE’s battery 

charger rulemaking refers to this mode as “maintenance.”

 Unplugged: When the mobile device is unplugged from its charger, but the charger remains 

plugged into the wall socket. If the user uses multiple chargers, then the energy consumption is 

due to all these chargers. DOE’s battery charger rulemaking refers to this mode as “no battery.”

 BC Unplugged: When the charger is unplugged from the wall socket. The power draw is 0W. 

To get representative estimates for power draw, we identified the 8 most popular tablets models and 

measured their power draw of 7 units using Watts Up? .Net and Yokogawa WT210 power meters. 

Measurements were taken after five seconds of the device entering the relevant operational mode and 

when the power draw has stabilized. Representative battery capacities and charger efficiencies were 

aggregated from review articles and manufacturer specifications of the selected device models. See 

Appendix Table B-8 for more details. 

We consider that users charge their mobile devices using the original (OEM) charger that came 

purchased with the product, and other chargers, such as after-market chargers, charging via the USB 

ports of PCs and speaker docks, and car chargers. Based on survey responses, we estimate that original 

chargers are used 90% of the time, and other chargers 10% of the time.
Fraunhofer USA Center for Sustainable Energy Systems 72

Table 3-52: Representative capacity and efficiency of original and aftermarket batteries and chargers for tablets.

Charger Type Relative 

Usage Time

Battery Capacity 

[Wh]

Charger Efficiency

[%]

Power Draw [W]

Idle*Unplugged

Original 90% 25.6 79% 0.36 0.08

Aftermarket 10% - 68% 0.40 0.13

Weighted Average - 25.6 78% 0.36 0.09

* Based on average measurements of several metered devices.

3.10.1.3.1 Charging

We calculate the energy consumption due to charging tablets by calculating the number of charge cycles 

per day, i.e., the number of full battery charges per day. This equals the product of the number of 

charge sessions per day, i.e., the number times the battery is charged in a day, and the average increase 

in battery charge level (from pre-charging to post-charging) for each charge session plus the added 

energy consumed due to charger losses (see Table 3-53). Our estimate of 0.44 charge cycles/day is 

higher than the estimate by DOE (2012) of 0.29 charges cycles/day, but similar to that of EPRI (2012) of 

0.5 charge cycles/day (every other day).

Table 3-53: Energy consumption estimates due to charging tablets.

Device Type

Battery Level Number Per Day Battery 

Capacity 

[Wh]

Charger 

Efficiency 

[%]

Energy Consumption

PreChargePostChargeCharge 

Sessions

Charge 

Cycles

Full Charge 

[Wh]

Per Day 

[Wh/day]

Primary 29% 95% 0.81 0.53 25.6 78% 33 16

Secondary*0.49 0.32 11

Weighted Average 29% 95% 0.67 0.44 25.6 78% 33 14

* Energy consumption and amount of charging estimated by the relative (weighted) usage between primary and secondary tablets (2.2 vs. 

1.4 hours). For example, the number of charge sessions = 2.2h×0.81 + 1.4h×0.49 / (2.2h + 1.4h) = 0.67.

3.10.1.3.2 Idle

We calculate the energy consumption due to the tablet being idle while plugged into the charger by 

multiplying the remaining time plugged in after charging to partial battery capacity in one day, and the 

power draw while idle. Tablet chargers do not charge at a constant rate for different battery levels; e.g., 

fast chargers charge faster at lower battery levels than higher levels. For simplicity we average the 

charging rates for <90% and ≥90% battery levels to estimate the average time to for a full charge, and 

assume a linear relationship for the time to partial charging. 

We estimate that 84% of tablets are charged only with the original charger, 11% are charged only with 

other chargers, and the remaining 5% of tablets are charged with both the original and other chargers. 

Our energy consumption estimate is lower than the 2010 estimate by DOE (2012) (0.9 vs. 5.3 Wh/day) 

because of our lower estimate for the time in idle mode (3.9 vs. 6.1 hours) and lower power draw (0.36 

vs. 0.87W).
Fraunhofer USA Center for Sustainable Energy Systems 73

Table 3-54: Energy consumption estimates of tablets in idle mode.

Device Type

Time [hr/day]

Power Draw 

[W]

Energy 

Consumption 

[Wh/day]

Connected to Charger Charging

Idle Original 

Charger Others All Chargers 0 to 100% Full [hr]

Per Day

[hr/day]

Primary 5.3 0.8 6.0 4.2 2.0 3.9 0.36 1.1

Secondary*3.2 0.5 3.6 1.4 2.8 0.8

Wt. Avg. 4.4 0.6 5.0 4.2 1.8 3.4 0.36 0.9

(DOE 2012) - - 7.5 - 1.4 6.1 0.87 5.3

* Energy consumption and amount of charging estimated by the relative usage between primary and secondary tablets (2.2 vs. 1.4 hours).

3.10.1.3.3 Unplugged

Tablets still contribute to energy consumption even when unplugged from the wall socket, because their 

chargers may still be plugged in. We estimate that, on average, original tablet chargers are plugged into 

the wall socket for 14 hours/day, but 49% of users leave the charger plugged in all of the time (24 

hours/day). Averaged over all tablets, including those that do not use another charger, “other” tablet 

chargers are plugged into the wall socket for 3 hours/day. Therefore, for tablets in the unplugged mode, 

the total energy consumption of their chargers is 0.9 Wh/day. Our estimates for time spent and the 

energy consumption for tablets in the unplugged mode are similar estimates by DOE (2012). Since we 

did not ask about secondary tablets, we assume that both primary and secondary tablet chargers are 

plugged into the wall socket for the same amount of time.

Table 3-55: Energy consumption estimate for tablets in unplugged mode.

Charger Type

Time [hr/day]

Power Draw 

[W]

Energy 

Consumption 

[Wh/day]

Charger Plugged 

Into Wall

Device 

Unplugged

Original Charger 14 8.5 0.08 0.7

Others*2.9 1.2 0.13 0.2

All Chargers 17 10 - 0.9

(DOE 2012) 16 8.5 0.13 1.1

* Since we did not ask about other chargers, we assume that if other chargers are used (>0 

hours/day), then they are left plugged in the same amount of time as the original charger.

3.10.1.4 Unit and Annual Energy Consumption (UEC and AEC)

Our calculations yield a UEC of 6.1 kWh/year for a typical tablet and an AEC of 0.61 TWh/year. Charging 

accounts for 86% of tablet UEC. Tablets with smaller screens (<8.9”) have a lower UEC, installed base, 

and AEC than tablets with larger screens (≥8.9”). Our estimates show that non-charging operational 

modes account for a notable portion of energy consumption (13%). Compared to portable PCs (see 

Section 3.5), we estimate that tablets have a UEC that is 8.8 times lower, a 11% higher installed base, 

and an AEC 8.2 times lower. If we assume that secondary tablets have the same usage and energy 

consumption as primary tablets, the UEC and AEC estimates would be 6.7 kWh/year and 0.67 TWh/year, 

respectively.
Fraunhofer USA Center for Sustainable Energy Systems 74

Figure 3-37: Energy consumption of tablets in different operational modes.

Table 3-56: UEC and AEC values for tablets.

Device Type

Energy 

Consumption

[Wh/day]

UEC [kWh/year] Installed 

Base*

[millions]

AEC

Charging Idle Unplugged Total [TWh/yr]

Small screen 12 3.6 0.4 0.3 4.2 32 0.14

Large screen 19 6.2 0.5 0.3 7.0 68 0.48

All Tablets 17 5.3 0.5 0.3 6.1 100 0.61

* Installed base for small and large screen tablets estimated by representative weights of selected most popular 

tablets scaled to the total installed base of tablets.

3.10.2 Comparison with Prior Energy Consumption Estimates

Our UEC estimates for several specific tablet models are slightly lower than estimates from other 

sources. Referring to our UEC and AEC estimates for desktop and portable PCs (see Sections 3.4 and 3.5,

respectively), we discuss some comparisons with those for tablets. While the plugged-in installed base 

of desktop and portable PCs have decreased since 2010 (by 13 and 39 million, respectively), the installed 

base for tablets has increased about 30-fold since 2010, i.e., from 4 million to 100 million. Thus, it 

appears that tablets are, to some extent, displacing some of the usage of desktop and portable PCs.

Applying our current UEC for desktop and portable PCs for our 2010 installed base estimates 

(Fraunhofer 2011), the AEC for desktop and portable PCs decreased by 2.5 and 1.9 TWh/year, 

respectively. On the other hand, applying our current UEC estimate for tablets, the AEC for tablets 

increased from 0.02 TWh/year to 0.6 TWh/year. This represents a net decrease in the total AEC of 3.7 

TWh/year for all computing devices, excluding smartphones.

Table 3-57: Current and prior energy consumption estimates for tablets.

Year Units

[millions]

UEC

[kWh/yr]

AEC

[TWh/yr] Device Model Source

2013 100 6.1 0.6 All tablets Current

2012 67†11.9 0.6† iPad 3 EPRI 2012

2012 - 7.2 - iPad 2 EPRI 2012

2012 - 7.1 - iPad 1 EPRI 2012

2012 - 8 - iPad 2 NRDC 2012

2010 2.5 - - iPad 1 Forrester 2010

† Based on sale reports of all iPads since Q2 2010 with no device retirement.

3.10.3 References

CEA. 2010. “12th Annual household CE Ownership and Market Potential.” CEA Market Research Report. 

Consumer Electronics Association. May, 2010. Consumer Electronics Association.

CEA. 2013a. “15th Annual CE Ownership and Market Potential Study.” CEA Market Research Report, 

April, 2013. Consumer Electronics Association.

0

5

10

15

20

Any tablet Small screen Large screen

Unplugged

Idle

Charging

Wh/d
Fraunhofer USA Center for Sustainable Energy Systems 75

CEA. 2013b. “U.S. Consumer Electronics Sales & Forecasts 2009-2014.” CEA Market Research Report, 

July, 2013. Consumer Electronics Association.

CEA. 2013c. Steve Koenig. Private correspondence, Nov. 2013. Consumer Electronics Association.

CEA. 2014. “Consumer Outlook on Tablets – Jan. 2014 Edition.” Jan. 2014. Consumer Electronics 

Association.

DRG. 2013. “United States PC, Tablet, & Mobile Phone Market Size and Forecast, Jul. 2013.” Daniel 

Research Group. 

http://www.danielresearchgroup.com/LinkClick.aspx?fileticket=1ejALRMAUbk%3D&tabid=122&mid=

522. Rerieved Oct. 30, 2013.

EPRI. 2012. “iPad Electricity Consumption in Relation to Other Energy Consuming Devices - Executive 

Summary.” Jun. 21, 2013. http://www.epri.com/OurWork/Documents/Energy%20Efficiency/iPadEnergyConsumeExecSummary6-2012Final.pdf. Retrieved 

Sept. 20, 2013.

Flurry Analytics. 2013. Khalaf, S. “Flurry Five-Year Report: It’s an App World. The Web Just Lives in It.” 

Apr. 3, 2013. http://blog.flurry.com/bid/95723/Flurry-Five-Year-Report-It-s-an-App-World-The-WebJust-Lives-in-It. Retrieved Nov. 12, 2013.

Forrester . 2010. Rotmann Epps, S. “U.S. Tablet Buyers Are Multi-PC Consumers.” Aug. 19, 2010. 

http://www.wired.com/images_blogs/gadgetlab/2010/08/US-Tablet-Buyers-Are-Multi-PCConsumers.pdf. 

FhCSE. Urban, Bryan, Kurt Roth, and Verena Tiefenbeck. 2011. “Energy Consumption of Consumer 

Electronics in U.S. Homes in 2010.” Final Report to the Consumer Electronics Association. 

http://www.ce.org/CorporateSite/media/Government-Media/Green/Energy-Consumption-of-CE-inU-S-Homes-in-2010.pdf. Dec.

Magid. 2013. “Tablets Find a Home in More U.S. Homes.” Jun. 9, 2013. 

http://www.magid.com/node/250. Retrieved Sept. 20, 2013.

Nielsen. 2013. “Q2 2013 Cross-platform report: viewing on demand.” Sept. 9, 2013. 

http://www.nielsen.com/us/en/reports/2013/q2-2013-cross-platform-report.html. Retrieved Oct. 

17, 2013.

NPD. 2013. “Internet Connected Devices Surpass Half a Billion in U.S. Homes, According to The NPD 

Group.” Mar. 18, 2013. NPD Group. https://www.npd.com/wps/portal/npd/us/news/pressreleases/internet-connected-devices-surpass-half-a-billion-in-u-s-homes-according-to-the-npdgroup/. Retrieved Jan. 24, 2014.

NRDC. 2012. Sullivan, D. “Consumer electronics programs: what can the Midwest do?” Jan. 12, 2012. 

Midwest Energy Solutions Conference 2012 presentation. http://mwalliance.org/sites/ 

default/files/uploads/meeaconference/MES-2012_presentations_Sullivan.pdf. Retrieved Feb. 2014.

Parks Associates. 2013. “Tablets: Disrupting Mobile Computing and the Digital Home.” Park’s Associates. 

Jul. 25, 2013. http://www.parksassociates.com/blog/article/pr-jul2013-tablets. Retrieved Sept. 2013.

Pew. 2013a. “Tablet Ownership 2013.” Jun. 10, 2013. 

http://www.pewinternet.org/~/media//Files/Reports/2013/PIP_Tablet%20ownership%202013.pdf. 

Retrieved 18 Sept. 2013.

Pew. 2013b. “Tablet and E-reader Ownership Update.” Jun. 10, 2013. 

http://www.pewinternet.org/~/media/Files/Reports/2013/PIP_Tablets%20and%20ereaders%20update_101813.pdf. Retrieved 18 Sept. 2013.
Fraunhofer USA Center for Sustainable Energy Systems 76

3.11 Set-top Boxes

3.11.1 Current Energy Consumption

Set-Top Boxes (STBs) receive and decode signals for playback on televisions. Features and services can 

vary according to service provider, subscription package, and device hardware, and may include high 

definition (HD) or standard definition (SD) tuners, video-on-demand, digital video recording (DVR)

capabilities, multiple tuners, format conversion, and more. We divide STBs into two major categories: 

pay TV STBs and standalone STBs. Pay TV STBs are generally leased to consumers by multichannel 

(cable, satellite, and telco23) TV providers and enable a variety of services and features. On the other 

hand, standalone STBs may be purchased directly by consumers, and generally provide alternative 

services to those of pay TV STBs. Standalone STBs include digital media streaming devices24, standalone 

DVRs, and OTA-DTAs. Digital media streaming adapters stream digital media from computer servers or 

the Internet to a television or audio system. DTAs are STBs that decode digital signals for TV viewing, 

and these exist in two forms: (1) cable digital transport adapters3that may decode digitally encrypted 

cable signals for viewing on subscriber TVs, and (2) over-the-air digital-to-analog adapters (OTA-DTAs) 

that decode unencrypted over the air digital broadcast signals transmitted via antenna for viewing on 

older analog TVs that lack a digital tuner.

Set-top box power draw depends on its features, and today there is more variety and complexity in 

features than ever before. In our prior study we divided subscription STBs into three feature categories: 

(1) DVR with any tuner; (2) non-DVR with Standard Definition (SD) tuner, and (3) non-DVR with High 

Definition (HD) tuner (FhCSE 2011). Since 2010, new device categories have emerged that affect power 

draw and usage. Among these are (4) multi-room/video server STBs that may have DVR capabilities; and 

(5) video client STBs that receive programming from multi-room server STBs. Some STBs, called thin 

clients, are designed to interface with and obtain content primarily from a multi-room video server STB 

or gateway that is connected directly to the service provider, rather than directly with the service 

provider. Since there are presently relatively few thin clients and video clients in service, we collectively 

label them thin clients in this study. 

Although there are relatively few manufacturers and models of STBs, the actual power draw of a specific 

device depends on what combinations of features are enabled for that particular household. Service 

providers can change the activated features of deployed STBs through software updates. For example, a 

service provider might launch multi-room DVR capability in compatible set-top boxes STBs through a 

software update. Some STBs include five or more tuners that can enable simultaneous viewing or 

recording of several programs, though not all of these tuners may be enabled or activated. While, such 

configuration decisions may influence power draw to some extent, there is limited publically available 

information about the distribution of features enabled by different providers. 

 

23 Other studies have referred to Telco TV as IPTV, but Telco TV includes subscription TV services that are not provided via IP, most notably 

Verizon FiOS. It does not include the streaming of video over an internet connection.

24 Sometimes called over-the-top (OTT) STBs, these refer to devices that receive media over the internet without a multiple system operator 

involved in content distribution. 
Fraunhofer USA Center for Sustainable Energy Systems 77

3.11.1.1 Installed Base 

To gain better understanding of the complex landscape of hardware and features, we conducted the CE 

Usage Survey to estimate the number of subscribers and different types of STBs in service. We 

combined those results with market research and industry specific data to estimate the feature 

distribution among households. 

3.11.1.1.1 Pay TV Set-top Boxes

The CE Usage Survey found that 95 million households subscribe to at least one multichannel video 

service (80% of all households, 83% of TV households). Of subscriber households, 91% claimed to have 

exactly one service, 8% two, and 1% three, for a total of 105 million TV subscriptions. Our survey results 

are comparable to other industry estimates, shown in Table 3-58. Since our survey appears to slightly 

over-represent cable and telco subscribers, we form a best estimate of the subscriber base by taking an 

average of values from Nielsen, SNL, and LRG sources25. 

We asked U.S. adults about STBs connected to their four most-viewed televisions, see Table 3-59. 

Because we asked only about STBs associated with the first four TVs, we assumed that the ratio of STBs 

to TVs was constant in a given household to make a reasonable upper-bound estimate26 of STBs per 

household. Thus, if a household had 8 TVs, and reported 3 STBs on the first four TVs, we would compute 

3STBs/4TVs x 8TVs = 6 STBs. Based on this analysis, we found that depending on service type there are 

between 1.3 and 2.3 STBs (DVR + non DVR) and 0.5 to 0.7 DVR STBs per subscriber household. About 

53% of subscriber households reported having at least one DVR, which is close to the 52-55% found by 

other industry sources (Nielsen 2013, LRG 2013d). Of reporting DVR households, we estimate that 90% 

had one, 8% had two, and 1% had 3 or more DVRs. 

Table 3-58: Pay TV customers by service, millions.

Table 3-59: Installed base of pay TV STBs by service (Nov. 2013 survey).

* Does not include cable DTAs. 

** Some subscribers have more than one service and some households are not subscribers.

All satellite and telco subscribers require at least one STB to receive any service in the home, but for 

cable customers this is not always true. Some cable providers offer basic unencrypted service, and 

customers can receive basic unencrypted service without any STBs. Other cable providers require either 

 

25 The original LRG data included subscribers from only the largest providers, which they claim account for 94% of all pay TV subscribers. We 

adjusted the cable values to include the missing 6%, since satellite and telco providers are principally comprised of two providers each. 

26 If we had instead assumed that households could have only a maximum of four STBs, the totals would be about 8% lower.

Service Survey 

Nov. 2013

Nielsen 2013

Q2 2013

SNL 2013b-c

Q2 2013

LRG 2013a-b 

Q3 2013 Estimate [%] of Total

Cable 62 56 55 56 56 55%

Satellite 31 34 34 34 35 34%

Telco 12 10 11 10 11 11%

Total 105 100 99 101 101 100%

Service Subscribers

[millions]

STBs per

Subscriber

STBs,

[millions]

[%] of Pay 

TV STBs

DVRs per

Subscriber

DVRs

[millions]

DVR:STB 

by Service

Cable*56 1.33 74 44% 0.49 28 37%

Satellite 35 1.99 69 41% 0.67 23 34%

Telco 11 2.32 25 15% 0.58 6 25%

Total/Wt.Avg.** 101 1.66 167 100% 0.56 57 34%
Fraunhofer USA Center for Sustainable Energy Systems 78

an STB or a cable DTA for viewing digitally encrypted channels or for viewing digital channels on analog 

televisions. The CE Usage Survey indicates that cable subscribers had the fewest STBs per household, 

compared with satellite and telco subscribers. Because of the survey question wording and because of 

the low number of STBs per cable household, it is unlikely that U.S. adults included cable DTAs in their 

responses. By 2013 there were about 28 million cable DTAs in service (SNL 2013a), and adding these to 

the cable STBs from our survey we find 1.8 STBs per cable household.

Survey responses suggest potential for misunderstanding among the STB questions27 , so these survey 

results should be considered only as approximate estimates of the installed base. First, about 28% of 

cable, 20% of satellite, and 30% of telco subscribers indicated they had no STBs, even though both 

satellite and telco customers require at least one STB to receive service. We excluded those unviable 

responses for satellite and telco subscribers when estimating STBs per subscriber. Second, about 5% of 

single-service subscribers indicated having both a DVR and non-DVR STB connected to the same TV. We 

counted these unusual responses as a single non-DVR STB, since they may represent the presence of a 

standalone DVR in conjunction with a pay-TV STB. We also assumed that households with a multi-room 

STB configuration had at most one DVR. Not doing so led to a DVR count that was about 27% higher 

than the SNL (2013a) estimate. Table 3-60 shows estimates from several sources by technology.28

Table 3-60: Installed base of pay TV STBs, millions.

SNL 2013a

Q2 2013

Survey 

Nov 2013

FhCSE 2011

Q2 2010 Notes

Cable Non DVR 58.6 46.6 50.3

SD 33.8 - 35.4

HD 24.7 - 14.9

IP Client 0.1 - -

DVR 26.8 27.5 22.5 No breakdown in survey by SD/HD.

SD 2.8 - -

HD 22.4 - -

IP Gateway 1.6 - -

Cable DTA 27.6 27.6 14.0 Not asked in 2013 survey, assume SNL value.

Satellite Non DVR 74.7 45.5 59.8

SD 44.2 - 49.2

HD 30.5 - 10.6

DVR 18.9 23.0 16.3 No breakdown in survey by SD/HD.

Telco Non DVR 21.8 18.6 12.1

SD 3.8 - 5.0

HD 18.0 - 7.1

DVR 10.2 6.1 3.7 No breakdown in survey by SD/HD.

Total 238.5 195.0 178.7

Subtotals Cable 113.0 101.7 86.8

Satellite 93.6 68.6 76.1

Telco 32.0 24.7 15.8

DVRs 55.9 56.6 42.5

Non-DVRs 182.7 138.4 136.2

Whole-home or multi-room STBs are growing in popularity and offer customers the flexibility of viewing 

or recording programming throughout their home without needing a fully-featured STB for each TV. We 

 

27 We asked participants to select all types of set top boxes connected to each of their TVs, including DVR STB, non-DVR STB, streaming media 

device with DVR, and streaming media device without DVR. It is likely that participants had trouble making the distinction among these devices. 

28 We do not consider the 0.6M digital cable ready devices that receive programming without an STB using a CableCARD (SNL 2013a).
Fraunhofer USA Center for Sustainable Energy Systems 79

asked pay TV subscribers about the multi-room features of their set top boxes. Households indicated if 

they could (1) record in one room and playback in another, (2) pause live TV and resume watching in 

another room, and (3) record five or more shows at once. Positive responses to either of the first two 

questions indicate that a household is likely to have a multi-room DVR setup, while the third indicates 

that at least one STB that is capable of serving multiple rooms. About 4% of U.S. adults reported having 

multi-room features (1) or (2) despite owning only one TV, so we counted these responses as singleroom DVRs. Many STBs ship with features that can be enabled through software updates issued by 

service providers. A major cable provider announced in Jun. of 2013 that it would be launching multiroom DVR capability to 8 million of its STBs through a software update (Multichannel 2013). This means 

that asking users about features may not always correctly identify multi-room STBs hardware if those 

features have not yet been activated or if the user is unaware such features exist. Still, we can use the 

responses to estimate the number of multi-room STBs. Table 3-61 shows our estimates for multi-room 

STBs among different service providers. Notably, a smaller portion of cable customers have a multiroom setup than do satellite and telco customers, partially because about 28% of cable households 

reported having no STBs installed. In total, we estimate that up to 26% of pay TV households have a 

multi-room setup (2 or more TVs and yes to questions (1) or (2)) and that 30.7% have at least one multiroom STB (1 or more TVs and yes to questions (1), (2), or (3)). We estimated the number installed by 

applying the percentage to the subscriber count, assuming at most one multi-room server STB per 

household. 

Table 3-61: Subscribers with multi-room STBs, millions (Nov. 2013 survey).

Cable Satellite Telco All

All Pay TV Subscribers 55.7 34.5 10.7 100.8

Multi-room households, % of subscribers 15.1% 34.7% 40.6% 25.9%

Multi-room ready households, % of subscribers 20.2% 40.0% 43.2% 30.7%

Multi-room server STBs 11.3 13.8 4.6 30.9

Table 3-62: Cumulative STB shipment projections from Q2-2010 to Q4-2013 (DOE 2013a).

Base

STB

Base 

DVR

MultiRoomMulti-Room

with DVR

Video 

Client Total Pct.

Cable 47.0 8.4 3.3 7.2 0.4 66.3 42%

Satellite 21.6 12.1 5.0 10.7 0.4 49.8 32%

Telco 5.8 2.1 0.8 1.8 0.6 11.1 7%

Thin Client 2.5 - - - - 2.5 2%

Digital Media Streaming 27.1 - - - - 27.1 17%

Total 104 22.6 9.1 19.7 1.5 156.8 100%

66% 14% 6% 13% 1% 100% -

* Thin clients are combined for cable and satellite providers. 

Pay TV STB shipments from the previous three years (DOE 2013a) totaled 127 million units, slightly more 

than half of the current installed base. STBs with servers totaled 29 million, of which 68% had DVRs. This 

total is consistent with the 31 million found in our survey, and as such, these data will be used to weight 

the power draw values in the subsequent analysis. In the DOE dataset, the video client category 

represents STBs that receive video from a multi-room video server STB. Since there are relatively few in 

service, we consider these with thin client STBs in our analysis. 
Fraunhofer USA Center for Sustainable Energy Systems 80

3.11.1.1.2 Standalone Set-top Boxes

Standalone STBs are those obtained independently of TV service providers, such as digital media 

streaming devices and standalone DVRs. Digital media streaming devices enable TV users to view 

content delivered over the Internet.

29 Though many newer smart TVs and Blu-ray players have this 

functionality built-in, here we are only concerned with non-integrated streaming devices.30

We estimate there were at most 40 million digital media streaming devices installed by the end of 2013 

– about four times higher than in 2010 (FhCSE 2011) – based on cumulative sales data from 2006-2013 

(CEA S&F 2013, BI 2014). Sales of the top three streaming media devices exceeded 15.2 million units in 

2013 and these make up more than 85% of the market (BI 2014). DOE forecasts for 2013 were lower, at 

10 million units (DOE 2013a). Our survey indicated that there were 57.1 million digital media streaming 

devices in service, and the average household had 0.48 such devices (1.7 devices per owner household, 

30% ownership). This is somewhat higher than a recent CEA survey (O&M 2013) that found 46.6 million 

digital streaming media devices (1.6 devices per owner household, 24% ownership). A 2013 survey of 

10,000 broadband households found that only 14% had a streaming media device (Parks 2013). Both 

survey estimates exceed the likely maximum installed base value and suggest potential confusion among 

consumers about what constitutes a digital streaming device. For instance, about 50% of owners 

reported that their streaming media devices had DVR capabilities; however the majority of devices do 

not offer this feature.

Standalone DVRs comprise a small part of the installed base, as most DVRs are integrated with 

subscription STBs. Standalone TiVo subscribers numbered 1 million in Q3 2013, down from a peak of 1.7 

million in 2007 (LRG 2013) and 1.5 million in 2010 (Gorman 2010). We estimate a similar decline in 

standalone DVRs from the 3 million in 2010, for a total of 2 million in 2013. 

Over-the-air (OTA) DTAs are devices that enable analog TVs to receive digital OTA broadcast signals. 

Since all new TVs must include a digital tuner, the number of these devices is expected to decline as 

older TVs are retired. An appreciable number of analog CRT TVs have been retired in the previous three 

years, and based on analysis of survey responses31 the number of households with at least one CRT TV 

was 60% lower in Dec. 2013 than in Aug. 2009 (CEA 2014, FhCSE 2009). We estimate that the installed 

base of OTA-DTA has declined at the same rate, and conclude that there are now 13 million units in 

service compared with 33 million units in 2010. 

Table 3-63: Installed base of standalone STBs, millions.

Device Units % of Standalone STBs

Digital Streaming 40.2 72.5%

Standalone DVR 2.0 3.6%

OTA-DTA 13.2 23.8%

Total 55.4 100%

 

29 Such as Netflix or Hulu.

30 Such as Apple TV, Roku, or Chromecast. 

31 As noted in the Television section of this report, people may incorrectly identify television types in surveys, so these numbers should serve 

only as approximate indicators. 
Fraunhofer USA Center for Sustainable Energy Systems 81

3.11.1.2 Unit Energy Consumption

STB power draw generally depends on its available features. We consider power draw across multiple 

feature categories including: provider type, ability to serve video content to multiple rooms (e.g., multiroom), HD or SD tuners, and DVR capability. STBs can have multiple tuners, allowing more than one TV 

to use the same STB simultaneously, or allowing viewers to record a program while watching another. 

Minimalist STBs, called thin-clients, draw less power than ordinary STBs by relying on a full-featured STB 

for their signal instead of communicating with the provider directly. 

STBs may have several power modes: (1) on- or active-mode, (2) sleep mode, and (3) deep sleep mode. 

Deep sleep is a sub-state of sleep mode that draws even less power, but may cause the device to require 

more time to respond when returning to active mode. Few STBs include a deep sleep mode, and many 

have similar power draw in both active and sleep modes. STBs lack a true off mode, and we believe it is 

uncommon for users to unplug or use power strips to completely power down STBs, since doing so may 

provoke a disruptive automatic reprogramming period. 

3.11.1.2.1 Power Draw

To determine power draw across providers, features, and usage modes, we relied on several sources. 

EPA (2012) provided measurements of on- and standby- mode power draw for many subscription STBs,

and we used these to represent STBs manufactured and installed since mid 2010, see Figure 3-38. We 

used the power draw values from (FhCSE 2011) to represent units manufactured before 2010. For each 

feature combination – provider, DVR/non-DVR, single/multi-room, HD/SD – we averaged power draw 

across the measured devices. We did not have access to the installed base data for each model, and 

were therefore unable to further refine our model by weighting power draw by the prevalence of 

specific models. Figure 3-38 shows how power draw varies among devices in similar categories.

Figure 3-38: Power draw of subscription set-top boxes by provider type and selected features, n=84 (EPA 2012).

Using a combination of installed base figures for 2010 (FhCSE 2011) and 2013 (based primarily on SNL 

data and secondarily on phone survey results), and industry sales data and projections (DOE 2013a, SNL 

2013a-c), we estimated the total number of devices of each type. We further subdivided the installed 

base for each category by year of manufacture (pre- or post- 2010) to enable power draw weighting by 

vintage. We retained the power draw values from FhCSE (2011) for standalone DVRs and OTA-DTAs. For 

digital streaming media devices, we used sales data (BI 2014) and power draw measurements (FhCSE 

2012, EPA 2012, AnandTech 2013, Roku 2011) to calculate a weighted average power draw by mode. 

0

10

20

30

on

sleep

has DVR

Cable Telco

DTA

single-room

multi-room

Satellite

thin client

multi-room

single-room

single-room

W

thin client
Fraunhofer USA Center for Sustainable Energy Systems 82

Next, we weighted power draw by manufacture date (pre- or post- 2010) to produce the estimates 

shown in Table 3-64 and Table 3-65. In cases where the sum of older devices (from 2010) and newly sold 

devices (from 2010-2013) was greater than the 2013 installed base (according to the FhCSE survey), we 

assumed that older devices were retired to account for this difference. In cases where the installed base 

in 2013 exceeded the sum of older devices and newly sold devices, we assumed that the projected sales 

figures were too low, and increased their number accordingly. 

Average32 on- and (standby-) mode power draw values were 15.6 W (13.7) for cable, 13.5 W (12.2) for 

satellite, and 12.9 W (11.1) for telco providers. These values are each about 1-2 W lower than in 2010, 

even as the portion of units with HD, DVR, and video streaming capabilities have increased.

Table 3-64: Power draw and installed base by device.

2010 Installed Base New Units from 2010-2013 2013 Installed Base

Installed Power Draw [W] Sales Power Draw [W] Installed Power Draw [W]

Type Features millions Active Sleep millions Active Sleep millions Active Sleep

Cable SD 35.4 16.5 15.9 27.1 15.6 13.1 31.0 15.7 13.4

HD 14.9 14.9 13.5 19.8 15.6 13.1 22.6 15.5 13.1

DVR (SD or HD) 22.5 29.6 27.3 8.4 20.8 17.0 19.6 25.8 22.9

Multi-room 0.0 NA NA 3.3 26.9 26.0 3.3 26.9 26.0

Multi-room+DVR 0.0 NA NA 7.2 25.5 22.1 7.2 25.5 22.1

Thin Client 0.0 NA NA 1.7 7.8 7.7 1.7 7.8 7.7

Cable DTA 14.0 4.4 4.4 13.6 4.8 4.7 27.6 4.6 4.5

Satellite SD 49.2 8.5 7.6 12.8 6.5 5.4 40.3 7.9 6.9

HD 10.6 20.7 18.2 8.8 11.3 10.0 27.8 14.9 13.1

DVR (SD or HD) 16.3 24.0 21.8 12.1 18.8 18.0 8.2 18.8 18.0

Multi-room 0.0 NA NA 5.0 23.5 21.8 5.0 23.5 21.8

Multi-room+DVR 0.0 NA NA 10.7 23.5 21.8 10.7 23.5 21.8

Thin Client 0.0 NA NA 1.7 6.6 5.5 1.7 6.6 5.5

Telco SD 5.0 10.7 10.5 1.0 9.4 9.1 3.5 10.3 10.1

HD 7.1 13.5 11.8 4.8 9.4 9.1 16.8 11.1 10.2

DVR (SD or HD) 3.7 19.3 14.9 2.1 15.8 12.3 8.4 17.3 13.4

Multi-room 0.0 NA NA 0.8 9.4 9.1 0.8 9.4 9.1

Multi-room+DVR 0.0 NA NA 1.8 15.8 12.3 1.8 15.8 12.3

Thin Client 0.0 NA NA 0.6 9.4 9.1 0.6 9.4 9.1

Standalone Digital Streaming 8.9 8.0 6.0 27.1 3.7 1.5 40.2 4.7 2.5

DVR 3.0 33.0 30.0 0 NA NA 2.0 33.0 30.0

OTA-DTA 33.0 6.5 0.8 0 6.5 0.8 13.2 6.5 0.8

Total/Weighted Avg. 223.6 14.2 12.2 170.4 13.4 11.5 294.0 12.8 10.9

Subtotals Cable 86.8 17.7 16.6 81.2 15.5 13.3 113.0 15.6 13.7

Satellite 76.1 13.5 12.1 51.0 15.5 14.2 93.6 13.5 12.2

Telco 15.8 14.0 12.1 11.1 11.6 10.2 32.0 12.9 11.1

Standalone 44.9 8.6 3.8 27.1 3.7 1.5 55.4 6.1 3.1

3.11.1.2.2 Usage and Consumer Behavior

The power draw of most pay TV STBs in 2013 varies weakly with power mode, so knowing precisely the 

number of hours spend in on vs. sleep mode does not strongly influence the energy consumption 

estimates. If deep sleep mode becomes more prevalent, or if light sleep begins to deliver deeper 

reductions in power, it may be necessary to develop updated estimates of time spent in each mode. 

 

32 Weighted average according to number of units in each device category.
Fraunhofer USA Center for Sustainable Energy Systems 83

Consequently, we continue to apply the usage estimates from FhCSE (2011) to calculate unit energy 

consumption, as shown in Table 3-65. 

3.11.1.2.3 Unit Energy Consumption

We estimate that, on average, pay TV STBs consume 119 kWh/yr and standalone STBs consume 

45 kWh/yr. Unit energy consumption (UEC) by device is given in Table 3-65. Cable units continued to 

consume more energy per device, at 128 kWh/yr, compared with 112 and 106 for satellite and telco, 

though most figures were lower than in 2010 – 20% lower for cable, no change for satellite, and 10% 

lower for telco. Cable saw the largest UEC decrease mainly because of the uptake of low-power cable 

DTAs. 

DVR-enabled STBs (including multi-room DVRs), account for about 37% of the total consumption of payTV STB energy use. Although their overall numbers have increased, their installed fraction remains 

steady at about 23% of the installed base of pay TV STBs, mainly due to the simultaneous increase in the 

number of cable DTAs. The UEC of DVR STBs has declined by about 16% since 2011. Multi-room server 

STBs consume on average 196 kWh/yr, account for about 20% of total pay-TV STB energy use, and 

comprise 12% of installed pay TV STBs.

3.11.1.3 Annual Energy Consumption

The total annual energy consumption (AEC) of all STBs is 31 TWh, Table 3-65. About 90% is attributed to 

pay TV STBs and 10% to standalone STBs. 

Figure 3-39: Summary of installed base, UEC and AEC for STBs.

0 10 20 30 40 50

SD

HD

DVR (HD or SD)

Multi-room

Multi-room + DVR

Thin Client

Cable DTA

SD

HD

DVR (HD or SD)

Multi-room

Multi-room + DVR

Thin Client

SD

HD

DVR (HD or SD)

Multi-room

Multi-room + DVR

Thin Client

Digital Streaming

DVR

OTA-DTA

Cable Satellite Telco

Standalone

millions

0 100 200 300

UEC [kWh/yr]

active sleep

0 2 4 6

AEC [TWh/yr]

0 50 100 150

Cable

Satellite

Telco

Standalone millions

0 50 100 150

active

sleep

UEC [kWh/yr]

0 10 20

AEC [TWh/yr]
Fraunhofer USA Center for Sustainable Energy Systems 84

Table 3-65: UEC and AEC summary for STBs.

Units [millions] Power Draw [W] Usage [h/day] UEC [kWh]

Type Features

2013 

Installed

Pre2010Post2010 Active Sleep Active Sleep Active Sleep TotalAEC

[TWh]

Cable SD 31.0 3.8 27.1 15.7 13.4 12.1 11.9 69.5 58.2 127.7 4.0

HD 22.6 2.8 19.8 15.5 13.1 12.1 11.9 68.6 56.9 125.6 2.8

DVR (HD or SD) 19.6 11.2 8.4 25.8 22.9 12.1 11.9 114.0 99.4 213.4 4.2

Multi-room 3.3 0.0 3.3 26.9 26.0 12.1 11.9 118.6 112.8 231.4 0.8

Multi-room+DVR 7.2 0.0 7.2 25.5 22.1 12.1 11.9 112.8 95.8 208.6 1.5

Thin Client 1.7 0.0 1.7 7.8 7.7 12.1 11.9 34.4 33.4 67.9 0.1

Cable DTA 27.6 14.0 13.6 4.6 4.5 24.0 0.0 40.3 0.0 40.3 1.1

Satellite SD 40.3 27.5 12.8 7.9 6.9 10.8 13.2 30.9 33.2 64.1 2.6

HD 27.8 10.6 17.2 14.9 13.1 10.8 13.2 58.7 63.3 122.0 3.4

DVR (HD or SD) 8.2 0.0 8.2 18.8 18.0 10.8 13.2 74.3 86.9 161.2 1.3

Multi-room 5.0 0.0 5.0 23.5 21.8 10.8 13.2 92.6 105.1 197.7 1.0

Multi-room+DVR 10.7 0.0 10.7 23.5 21.8 10.8 13.2 92.6 105.1 197.7 2.1

Thin Client 1.7 0.0 1.7 6.6 5.5 10.8 13.2 26.0 26.5 52.5 0.1

Telco SD 3.5 2.5 1.0 10.3 10.1 13.2 10.8 49.8 39.8 89.6 0.3

HD 16.8 7.1 9.7 11.1 10.2 13.2 10.8 53.7 40.3 94.0 1.6

DVR (HD or SD) 8.4 3.7 4.7 17.3 13.4 13.2 10.8 83.5 52.9 136.4 1.1

Multi-room 0.8 0.0 0.8 9.4 9.1 13.2 10.8 45.3 35.8 81.2 0.1

Multi-room+DVR 1.8 0.0 1.8 15.8 12.3 13.2 10.8 76.0 48.4 124.4 0.2

Thin Client 0.6 0.0 0.6 9.4 9.1 13.2 10.8 45.3 35.8 81.2 0.1

Standalone Digital Streaming 40.2 8.9 31.3 4.7 2.5 21.6 2.4 36.7 2.2 38.9 1.6

DVR 2.0 2.0 0.0 33.0 30.0 11.5 12.5 138.5 136.9 275.4 0.6

OTA-DTA 13.2 13.2 0.0 6.5 0.8 10.8 13.2 25.6 3.9 29.5 0.4

Total/Weighted Avg. 294.0 107.4 186.6 12.8 10.9 14.2 9.8 59.1 45.8 104.9 30.8

Subtotals Cable 113.0 31.8 81.2 15.6 13.7 15.0 9.0 73.6 54.5 128.1 14.5

Satellite 93.6 38.1 55.5 13.5 12.2 10.8 13.2 53.2 58.7 111.9 10.5

Telco 32.0 13.3 18.7 12.9 11.1 13.2 10.8 61.9 43.8 105.8 3.4

Standalone 55.4 24.1 31.3 6.1 3.1 18.7 5.3 37.7 7.4 45.2 2.5

3.11.2 Comparison with Prior Energy Consumption Estimates

Our pay TV STB energy use estimate of 28.3 TWh/yr is about 18% higher than our prior estimate of 

24 TWh/yr (FhCSE 2011) and close to that of 27 TWh/yr (NRDC 2011), both for 2010. The adoption of 

new features, such as HD, DVR, and multi-room video server, and the overall increase in deployed STBs 

is driving changes in STB energy consumption in the pay TV category. Even as new features become 

adopted, the power draw of individual devices categories appears to be on a slight decline (see Table 

3-64). Figure 3-40 and Figure 3-41 show trends in device sales. Annual sales of pay TV STBs is about 33 

million units per year, suggesting an average product lifespan of about 7 years, based on a 238 million 

unit installed base. 

In Dec. 2012, fifteen multichannel video providers and STB manufacturers signed a voluntary agreement 

that aims to reduce the energy consumption of set-top boxes (NCTA 2014). As part of the agreement, 

90% of devices purchased after Jan. 1, 2014 will need to meet ENERGY STAR v3.0 efficiency standards. In 

Dec. 2013, a non-regulatory consensus agreement was signed with the addition of efficiency advocates, 

and endorsed by DOE, that added an additional Tier 2 requirement for 2017 (NCTA 2014). According to 

DOE (2013), “these new standards – developed through a voluntary agreement between the pay-TV 

industry, the consumer electronics industry, and U.S. Energy Advocacy organizations (NRDC, ACEEE) –

will improve set-top box efficiency by 10-45% (depending on box type) by 2017.” The voluntary 

agreement also includes additional energy efficiency provisions, including light sleep capabilities, 
Fraunhofer USA Center for Sustainable Energy Systems 85

automatic power down features, and whole-home DVR solutions being made available as an alternative 

to multiple in-home DVRs for subscribers. These changes will likely affect energy consumption going 

forward and will need to be considered in future analyses.

In the standalone STB category, the major shift is a large increase in the installed base of digital media 

streaming devices. Power draw for these devices, while already low, has declined slightly from 2010. 

Comparisons with prior estimates are given in Table 3-66 and Table 3-67. 

Table 3-66: Prior energy consumption estimates for subscription STBs.

Year Units Power [W] Usage [h/yr] UEC AEC Source [millions] Active Off Active Off [kWh/yr] [TWh/yr]

Cable

2013 113 16 14 5,475 3,285 128 14.5 Current

2010 87 18 17 4,526 4,234 150 13.0 FhCSE 2011

2008 52 - - - - 173 9.0 LBNL 2010

2006 77 16 15 2,730 6,030 134 10.0 TIAX 2007

2003 35 16 16 1,825 6,935 140 4.9 NRDC 2005

2003 - - 23 2,555 6,205 - - DEG 2004

2003 65 23 22 - - - - ACEEE 2004

2000 49 13 11 - - 103 5.0 LBNL 2001

Satellite

2013 94 14 12 3,941 4,819 112 10.5 Current

2010 76 14 12 3,941 4,819 112 8.5 FhCSE 2011

2008 51 - - - - 206 10.5 LBNL 2010

2006 70 15 14 3,240 5,520 129 9.0 TIAX 2007

2003 32 - - - - - - NRDC 2005

2003 - - 16 2,555 6,205 - - DEG 2004

2003 32 18 17 - - - - ACEEE 2004

2000 13 17 16 - - 140 1.9 LBNL 2001

Telco

2013 32 13 11 4,834 3,926 106 3.4 Current

2010 16 14 12 4,834 3,926 115 1.8 FhCSE 2011

2008 3 - - - - 164 0.5 LBNL 2010

Table 3-67: Prior energy consumption estimates for standalone STBs.

Year Units Power [W] Usage [h/yr] UEC AEC Source [millions] Active Off Active Off [kWh/yr] [TWh/yr]

Digital 

Streaming

2013 42 4.7 2.5 7,884 876 36 1.6 Current

2010 9 8.0 6.0 7,884 876 68 0.6 FhCSE 2011

OTA-DTA

2013 13 6.5 0.8 3,942 4,818 29 0.4 Current

2010 33 6.5 0.8 3,942 4,818 29 1.0 FhCSE 2011

2008 35 6.5 0.8 4,745 4,015 27 0.9 LBNL 2011

DVR

2013 2.0 33 30 4,198 4,562 275 0.6 Current

2010 3.0 33 30 4,198 4,562 275 0.8 FhCSE 2011

2006 1.5 27 27 2,080 6,680 237 0.4 TIAX 2007

2003 - 24 24 - - - - NRDC 2005
Fraunhofer USA Center for Sustainable Energy Systems 86

Figure 3-40: Annual STB sales to dealers by display technology. 

Figure 3-41: Cumulative STB sales to dealers by display technology since 2005.

3.11.3 References

ACEEE. Amann, J.T. 2004. “Set-top boxes: Opportunities and issues in setting efficiency standards.” 

American Council for an Energy-Efficient Economy. Report No. A041. Jul. 

AnandTech. 2013. Google Chromecast Review. http://www.anandtech.com/show/7186/googlechromecast-review-an-awesome-35-hdmi-dongle/2. Retrieved Mar. 2014.

BI. Hoelzel, Mark. 2014. “The Connected TV Landscape.” Business Insider Australia. 

http://www.businessinsider.com.au/the-connected-tv-landscape-why-smart-tvs-and-streaminggadgets-are-conquering-the-living-room-2014-2. Feb.

CEA S&F. 2013. “U.S. Consumer Electronics Sales & Forecasts 2009-2014.” CEA Market Research Report. 

Consumer Electronics Association. Jul.

CEA O&M. 2013. “15

th Annual Household CE Ownership and Market Potential.” CEA Market Research 

Report. Consumer Electronics Association. May.

CEA. 2014. “CRT Television Ownership and Usage Update.” Consumer Electronics Association. Jan.

DEG. 2004. “Analysis of standards options for consumer electronics standby losses.” Codes and 

Standards Enhancement Initiative for PY2004: Title 20 Standards Development. Davis Energy Group 

Report for Gary Fernstrom, Pacific Gas and Electric Company. May.

DOE. 2013a. “National Impact Analysis.” Rulemaking for Set-top Boxes Energy Conservation Standards 

and Test Procedure. U.S. Department of Energy. http://www1.eere.energy.gov/buildings/ 

appliance_standards/rulemaking.aspx/ruleid/33. Retrieved Feb. 2014. 

DOE. 2013b. “U.S. Energy Department, Pay-Television Industry and Energy Efficiency Groups Announce 

Set-Top Box Energy Conservation Agreement; Will Cut Energy Use for 90 Million U.S. Households, 

Save Consumers Billions” U.S. Department of Energy. Dec. 

EPA. 2012. Draft 2 Version 4.1 Set Top Box Dataset. U.S. Environmental Protection Agency. http://www 

.energystar.gov/products/specs/sites/products/files/Draft_2_Version_4_1_Set_top_Box_Dataset.xlsx

0

10

20

30

40

2005 2007 2009 2011 2013

Digital Strm.

Telco

Satellite

Cable

STBs sold annually [millions]

0%

20%

40%

60%

80%

100%

2005 2007 2009 2011 2013

Portion of annual sales

0

100

200

300

2005 2007 2009 2011 2013

Digital Strm.

Telco

Satellite

Cable

STBs sold since 2005 [millions]

0%

20%

40%

60%

80%

100%

2005 2007 2009 2011 2013

Portion of sales since 2005
Fraunhofer USA Center for Sustainable Energy Systems 87

FhCSE. Roth, Kurt and Bryan Urban. 2009. “Assessment of the Energy Savings Potential of Policies and 

Measures to Reduce Television Energy Consumption.” Final Report to the Consumer Electronics 

Association. Fraunhofer Center for Sustainable Energy Systems. Oct.

FhCSE. Urban, Bryan, Kurt Roth, and Verena Tiefenbeck. 2011. “Energy Consumption of Consumer 

Electronics in U.S. Homes in 2010.” Final Report to the Consumer Electronics Association. 

http://www.ce.org/CorporateSite/media/Government-Media/Green/Energy-Consumption-of-CE-inU-S-Homes-in-2010.pdf. Dec.

FhCSE. 2012. Craig Akers, Linda Mayer, and Kurt Roth. Power Measurements of Selected Set Top Boxes. 

Gorman, Bill. 2010. “TiVo loses 96,000 subscribers in most recent quarter.” TV by the Numbers. http:// 

tvbythenumbers.com/2008/05/28/quarterly-net-new-tivo-subscribers-2001-april-2008/3945. May.

LBNL. Cheung, H.Y., A.Meier, and R.Brown. 2011. Energy savings assessment for digital-to-analog 

converter boxes. Lawrence Berkeley National Laboratory. Prepared for U.S. Department of Energy. 

Mar.

LBNL. Rosen, K., A. Meier, and S. Zandelin. 2001. “Energy use of set-top boxes and telephony products in 

the U.S.” Lawrence Berkeley National Laboratory. Report No. LBNL-45305. Jun. 

LBNL. Sanchez, Marla, Steven Lanzisera, Bruce Nordman, Alan Meier, Rich Brown. 2010. “EEDN: Set top 

box market assessment report.” Lawrence Berkeley National Laboratory. Feb. 

http://efficientnetworks.lbl.gov/pubs/EEDN_task_2-4-1_STB_Market_Assessment_Report.pdf. 

LRG. 2013a. “Major Multi-Channel Video Providers Lost About 25,000 Subscribers in Q3 2013.” 

Leichtman Research Group. http://www.leichtmanresearch.com/press/111813release.html. Nov. 

LRG. 2013b. Major multi-channel video providers lost about 345,000 subscribers in 2Q 2013. 

FierceCable. http://www.fiercecable.com/press-releases/major-multi-channel-video-providers-lostabout-345000-subscribers-2q-2013. Aug. 

LRG. 2013c. “The Rise and Plateau of DVRs.” 

http://www.leichtmanresearch.com/research/notes12_2013.pdf

LRG. 2013d. “DVRs Leveling Off at About Half of All TV Households.” 

http://www.leichtmanresearch.com/press/120613release.html. 

Multichannel News. Jeff Baumgartner. 2013. “Comcast Tees Up Multi-Room DVR for X1.” 

http://www.multichannel.com/distribution/comcast-tees-multi-room-dvr-x1/143670. Jun.

NCTA. 2014. Voluntary Agreement for Ongoing Improvement to the Energy Efficiency of Set-Top Boxes.

http://www.ncta.com/energyagreement. National Cable and Telecommunication Association.

Nielsen. 2013. “The Cross-Platform Report | Q2 2013.” Sept. 

NRDC. Foster, S. 2005. “Cable and Satellite set-top boxes: opportunities for energy savings.” Ecos 

Consulting report for the Natural Resources Defense Council. Mar. 

NRDC. Horowitz, Noah. 2011. Better viewing, lower energy bills, and less pollution: improving the 

efficiency of television set-top boxes. National Resources Defense Council. Jun. 

Roku. 2011. “Roku’s Power Consumption when Idle.” Roku Forums. http://forums.roku.com/ 

viewtopic.php?p=287461&sid=08c945a0ae6dc63df0d99a9e52d1cd13. Retrieved Mar. 2014. 

SNL. 2013a. Set Top Box Installed Base. Private communication of industry research. SNL Kagan. Nov.

SNL. 2013b. SNL Kagan Releases 2nd-Quarter U.S. Multichannel Subscriber Report. SNL Kagan. PR Web. 

http://www.prweb.com/releases/2013/9/prweb11070470.htm. Sept.

SNL. 2013c. “U.S. Multichannel Subscriber Update and Programming Cost Analysis.” SNL Kagan White 

Paper. Jun. 
Fraunhofer USA Center for Sustainable Energy Systems 88

3.12 Televisions

3.12.1 Current Energy Consumption

Televisions continue to be the most widely owned consumer electronic device in the U.S. at 97-98% 

household penetration in 2013 (CEA O&M 2013, 2013 CE Usage Survey ). TV energy consumption varies 

with display type, screen size, and year of manufacture. High-definition flat-panel displays continue to 

dominate the marketplace (74% household penetration), while displays with ultra-high definition (UHD) 

are now becoming available. Newer features such as Internet capable TVs and 3DTVs are increasing in 

popularity, with 15% and 9% household penetration (CEA O&M 2013). At the same time, unit energy 

consumption is declining due to improvements in display technologies. 

As in prior studies, our TV energy use estimates are based primarily on usage and ownership data from 

the CE Usage Survey, manufacturer-reported power draw measurements, and industry sales data.

3.12.1.1 Installed Base

Televisions slightly outnumber people in U.S. homes with 338 million owned (CEA O&M 2013) and 301 

million plugged in (2013 CE Usage Survey ). A review of recent TV ownership surveys is presented in 

Table 3-68. Figure 3-42 shows the distribution of TVs per household for 2013 and 2010.

Table 3-68: Installed base estimates for TVs in 2013.

Year Household 

Penetration

Households

[millions]

Units/Owner 

Household

Installed Base 

[millions] Sources

2013 96.8% 119 2.6 301*2013 CE Usage Survey 

2013 98.0% 119 2.9 338 CEA O&M 2013

2012 99.0% 119 2.9 340 CEA O&M 2012

2011 96.0% 119 3.0 343 CEA O&M 2011

2010 99.0% 116 3.1 353*CE Usage Survey Oct-2010 

2010 99.1% 116 2.9 328 Nielsen 2010

2010 95.0% 114 3.0 325 CEA O&M 2010

2009 95.8% 116 2.4 271** CE Usage Survey Aug-2009

2009 99.0% 114 3.0 339 CEA O&M 2009

2009 99.2% 115 2.9 335 Nielsen 2010

* Indicates TVs that were plugged into an electrical outlet during the past month.

** Indicates TVs that were used to watch television at least once in the past week.

Figure 3-42: TV ownership distribution (CE Usage Survey).

Plugged-in TVs appear to have declined by 50 million units or 14% since 2010, and while sharp, this 

decrease may be reasonable. Previous estimates place household TV ownership in slight excess of the 

U.S. population. It is plausible that many older and lesser-used TVs (primarily CRTs) are being discarded 

3%

29% 28%

20%

11%

5%

2% 1% 0% 0% 1%

0%

10%

20%

30%

0 1 2 3 4 5 6 7 8 9 10+

2010 2013

TVs per household
Fraunhofer USA Center for Sustainable Energy Systems 89

without being replaced. Nielsen found that about 1 million households own no TVs (Nielsen 2013), while 

our survey indicated this was closer to 4 million. Even though the number of households has increased 

from about 116 to 119 million households, the number owning at least one TV has remained constant at 

about 115 million. 

According to EPA estimates, 23.6 million TVs were disposed of in 2010 and a further 28.5 million were 

ready for end of life management (EPA 2011). Assuming a consistent disposal rate during the 3.5-year 

period since the 2010 study, 83-100 million TVs would have been removed from the installed base 

during this period. Consistent with that, a recent phone survey-based study of CRT TVs in U.S. 

households estimated that during the past five year 91 million CRT TVs were disposed by U.S. 

households (CEA 2014).During the same 3.5 year period, sales to dealers were 131 million units (CEA 

S&F 2013), which is at least enough to maintain prior installed base levels. 

U.S. adults indicated the display technology and screen size of their four most-used TVs. Though many 

display types exist, we limited the options to avoid confusion. The LCD category represents both LED, 

OLED, and fluorescent lit displays. Consumers did not know or specify their display type for 13% of TVs 

and screen size for 4% of TVs. Our survey and modeling identified 80 million CRTs plugged in in U.S 

homes in 2013.For comparison, CEA (2014) found that 41 percent of households had at least one CRT 

TV, with an average of 1.86 CRT units per household. This yields a total of 91 million CRT TVs in homes

including units in storage, in February 2014. 

To verify the consistency of survey reported screen sizes, we compared the distribution reported size 

with sales data from an industry source for TVs sold from 2010-2012. LCD screen size agreed very well; 

however, many people reported owning plasma displays smaller than 35 inches even though nearly all 

plasma displays are greater than 37 inches. Historically, survey-based plasma ownership estimates have

been higher than cumulative sales figures (FhCSE 2011), necessitating some adjustment. To compensate, 

we reclassified all reported plasma displays with screen sizes 37 inches or below as LCD TVs. In total we 

reclassified 15.3 million plasma TVs as LCD TVs, which greatly improved the plasma TV size distribution’s 

agreement with sales data, without appreciably affecting the already good agreement of the LCD screen 

size distribution, see Figure 3-43. The breakdown of TVs by display type is given in Table 3-69.

Figure 3-43: Screen size for LCD and Plasma TVs from 2010 to 2012. Reclassifying survey responses for Plasma TVs of 37 in. or 

lower as LCD TVs improves survey agreement with sales data. 
Fraunhofer USA Center for Sustainable Energy Systems 90

Table 3-69: Distribution of TVs by display type. Figure 3-44: TVs by display type.

Source LCD Plasma CRT Proj.

2013 FhCSE Model 63% 7% 27% 4%

2013 Nov. CE Usage Survey 57% 12% 27% 4%

2013 CEA O&M Survey 39% 19% 42% -

2010 FhCSE Model 33% 7% 54% 6%

2010 CEA O&M Survey 21% 13% 62% 5%

2009 Aug. CE Usage Survey 25% 7% 62% 5%

TV size continues to increase, with an average diagonal screen size of 34 inches, up from 29 inches in 

201033 (FhCSE 2011) and 26 inches in 2006 (TIAX 2007). In Figure 3-45 we show the distribution of 

screen size and age according to the Aug. 2009 survey. Primary TVs, those used most in a household, are 

substantially larger at about 41 inches (38 in 2010). TVs averaged about 5.5 years old (6.2 in 2010)34

according to the CE Usage Survey. 

Figure 3-45: TVs by screen size and age (Nov. 2013 survey). Bin ranges not of equal size.

Usage patterns greatly affect TV energy consumption estimates, and newer, larger TVs tend to be used 

more frequently than older, smaller ones. We accounted for usage patterns by assigning TVs to a “usage 

priority group” where TV1 is the most used TV in a household, TV2 is the second most used, and so on. 

The assignments, based on survey responses, are indicated in Figure 3-46.

 

33 Average display size is approximate. In the 2013 survey, responders gave their best estimate in inches, while in 2010, we asked only about 

discrete size ranges.

34 The figure was obtained by assuming that TVs in the 15+ category were exactly 15 years old. Since discrete size ranges were recorded, 

average age is approximate.

188

20

81

11

0

50

100

150

200

LCD Plasma CRT Proj.

Millions 2010 2013

3% 5%

20%

14%

28%

21%

10%

0%

10%

20%

30%

<14 14-18 19-24 25-31 32-41 42-51 51+

Percentage of TVs 2010 2013

Diagonal Screen Size [in.]

18%

38%

23%

12%

9%

0%

10%

20%

30%

40%

<1 2-4 5-9 10-14 15+

Percentage of TVs 2010 2013

Age in Years
Fraunhofer USA Center for Sustainable Energy Systems 91

Figure 3-46: Distribution of TVs by display technology and usage priority.

3.12.1.2 Unit Energy Consumption

3.12.1.2.1 Power Draw

Since our previous study in 2010, two new ENERGY STAR specifications have gone into effect (v5.3 and 

v6.0), setting more stringent requirements for maximum on mode power draw based on screen area 

and summarized in Table 3-70 (EPA 2013). ENERGY STAR-compliant TVs accounted for 84% of the units 

sold in 2012 and 96% in 2011 (EPA 2010-12). 

Table 3-70: ENERGY STAR power draw requirements for TVs.

ENERGY 

STAR

Screen Area 

[in2]

Max. On Mode

Power [W]

Max. Sleep 

Power [W] Manufacture Date

v6.0 A Pmax = 100∙tanh(0.00085∙(Α–140) + 0.052) + 14.1 1.0 May 15, 2013

v5.3 A < 275 Pmax = 0.130∙A + 5 1.0 May 1, 2012

v5.3 275≥ A ≥ 1068 Pmax = 0.084∙A + 18 1.0 May 1, 2012

v5.3 A > 1068 Pmax = 108 1.0 May 1, 2012

v4.0 A < 275 Pmax = 0.190∙A + 5 1.0 May 1, 2010

v4.0 A ≥ 275 Pmax = 0.120∙A + 25 1.0 May 1, 2010

We assessed TV power draw as a function of display type, screen size, and production year, developing 

linear regressions based on several data sources, see Table 3-71. For TVs sold until 2010, we used power 

regressions from our 2010 study (FhCSE 2011). For TVs sold between 2010 and 2013, we developed new 

regressions from a combination of California Energy Commission appliance database (CEC 2013) and the 

EPA ENERGY STAR list of qualified TVs (EPA 2013). The CEC database provides active mode power draw 

and linear screen size (n= 4,829 models, 96% LCD or OLED and 4% Plasma), but it does not provide year 

of manufacture or standby power draw. Of the listed units, 69% of LCD displays had active mode power 

draw that met ENERGY STAR v5.3 (95% for v4.0), while 37% of Plasma displays met v5.3 (89% for v4.0). 

These compliance levels suggest that the CEC database is representative of TVs sold during the 2011-

2013 period, and we use their values to generate new linear active mode power regressions given in

Table 3-71. 

The ENERGY STAR 6.0 draft development dataset (n=430, 83% LCD, LED, or OLED; 17% Plasma) includes 

ENERGY STAR qualified TVs on the market in Q4 of 2010 through 2011 (EPA 2013). Off-mode power 

draw for these TVs averaged 0.27 W, and the current list (Dec 2013) of qualified TVs contains 998 

models, for which the average standby mode power draw is 0.29 W. These figures are slightly lower 

0%

10%

20%

30%

40%

TV1 TV2 TV3 TV4 TV5 TV6+

2013

Projection

Plasma

LCD

CRT

0%

10%

20%

30%

40%

TV1 TV2 TV3 TV4 TV5 TV6+

2010

Projection

Plasma

LCD

CRT
Fraunhofer USA Center for Sustainable Energy Systems 92

than the 0.41 W found in the 2010 study. For TVs made prior to 2008, we assume 4 W for off-mode 

power draw (TIAX 2008).

The ENERGY STAR v6.0 draft 2 development dataset (n=1,697, 94% LCD+LED+OLED and 6% Plasma) 

includes active but not standby power draw for ENERGY STAR qualified TVs that went on the market in 

Q1 2011 through Q2 2012 (EPA 2013).

Table 3-71: Active mode power regressions by TV screen area, display, and production year.

Figure 3-47: Power regressions for LCD and Plasma TVs (CEC 2013).

Internet connected TVs, if they remain connected during standby mode, could significantly increase 

energy consumption; one model drawing 24W in inactive mode compared with less than 1 W for most 

non-connected TVs (NRDC 2012). About 3% of TVs in the v6.0 development dataset offered Internet

connectivity, though there were insufficient power draw data for connected-standby mode. It is also 

unknown what portion of Internet ready TVs are (1) connected to the Internet and (2) maintain their 

connection while the display is off, both of which would affect the standby power draw. Internet 

capable TVs have a 15% household penetration as of 2013 (CEA O&M 2013).

0

100

200

300

400

0 1000 2000 3000

CEC non-ES 5.0

CEC ES 5.0

[in2]

W LCD TVs

0

100

200

300

400

0 1000 2000 3000

CEC non-ES 5.0

CEC ES 5.0

[in2]

W Plasma TVs

P[W]=C1+C2∙A[in2]

Display Year C1 C2 R

2

N Source

LCD 2011-3 ES 16.47 0.05 0.74 3,208 CEC

2011-3 non-ES 28.59 0.10 0.69 1,419 CEC

2011-3 ALL*12.58 0.08 0.54 4,627 CEC

2010*24.06 0.09 0.71 123 Fraunhofer 2010

2009 17.15 0.17 0.74 98 Fraunhofer 2010

2008 11.59 0.20 0.91 99 Fraunhofer 2010

2008-9

*

15.98 0.18 0.81 197 Fraunhofer 2010

2005-7

*

19.23 0.25 0.93 121 ENERGY STAR

Plasma 2011-3 ES 52.19 0.04 0.42 72 CEC

2011-3 non-ES 105.50 0.04 0.15 124 CEC

2011-3 ALL*58.26 0.06 0.24 196 CEC

2010*4.77 0.14 0.53 24 Fraunhofer 2010

2009 -15.78 0.24 0.91 22 Fraunhofer 2010

2008 35.32 0.21 0.90 19 Fraunhofer 2010

2008-9

*

8.48 0.22 0.89 41 Fraunhofer 2010

2005-7

*

80.54 0.29 0.58 33 ENERGY STAR

Projection 2005-7

*

87.45 0.07 0.61 10 ENERGY STAR

CRT 2006*59.97 0.10 0.91 - TIAX 2007

* Regression used in the energy model. Other data provided for reference.

ES=ENERGY STAR qualified product; non-ES=Non ENERGY STAR qualified product; ALL=ES + non-ES products.
Fraunhofer USA Center for Sustainable Energy Systems 93

TV power draw may be influenced by other factors, such as screen resolution, brightness settings, and 

other features, though without better installed base and power draw data, these factors could not be 

evaluated. For instance, Figure 3-48 shows how much more power is needed in a bright room vs. the 

baseline of a dark room, when using automatic brightness control. On average, power draw was about 

50 W higher and nearly twice for the bright room case. About 70% of TVs in the ENERGY STAR v6.0 

development dataset offer automatic brightness control, though it is not clear how many users actually 

implement this feature (EPA 2013), adding some uncertainty to the actual power draw measurements.

Figure 3-48: Impact of TV brightness on power draw (EPA 2013).

3.12.1.2.2 Usage

Average usage per-TV appears steady at 3.2 h/day (5.2 for the primary TV), while on-time has increased 

slightly to 4.4 h/day (from 3.8 in Aug. 2009). This apparent 10% increase in unit on-time was more than 

offset by the 14% decrease in the installed base during the same period, suggesting a 4% decrease in 

total TV active usage.

We determined usage from the CE Usage Survey. Active usage includes the time when users engage in 

any TV-related activities (viewing TV, DVD, game consoles, etc.), while “on time” also includes the time 

when the TV is left on but unused. Our surveys asked for the usage of the four most used televisions per 

household. We derived usage estimates for lesser-used TVs using a proportional scaling35 by usage 

priority. The precision of usage estimates for TVs beyond the four most-used per household is not so 

important, since we estimate they represent only a small portion of the total usage (3%) and installed 

base (11%). Their usage occurs mainly in the off mode, so energy estimates for these lesser-used TVs is 

more sensitive to off-mode power draw and less sensitive to active mode usage and power draw 

estimates. 

Lawrence Berkeley National Laboratory (LBNL) calculated TV usage profiles from Nielsen’s metered 

usage data in over 12,000 representative U.S. households from May 2007 to 2011 (DOE 2012). Metering 

devices were installed on each TV of a participating household and measured TV on-time for each TV, 

though TVs that were not used at all were excluded from the dataset. They found that the average TV 

viewing time was 5.5 h/day, about 7 h/day for primary TVs and less than 2.5 h/day for non-primary TVs. 

 

35 For each TV display category, we calculated the average usage for TVs 4 and 5 using a proportional scaling by TV usage priority (e.g., usage of 

TV5 = average(TV1/TV2, TV2/TV3, TV3/TV4)∙TV4). 

0

50

100

150

200

250

300

TVs, n=301

Bright Room - 300 Lux

Dark Room - 0 Lux

W

0

100

200

300

0 100 200 300

Bright Room - Dark Room [W]

Bright Room Mode [W]
Fraunhofer USA Center for Sustainable Energy Systems 94

These values are generally similar to our values of 7.0 and 2.9 h/day for primary and non-primary TVs, 

respectively. The LBNL study also compared results with data from the 2009 Renewable Energy 

Consumption Survey (EIA 2011) and noted that the survey method produced lower usage values than 

the Nielsen data set, which was based on in-home metering of TV on-time. According to Nielsen (2013), 

per-person TV usage in 2013 amounts to 5.6 h/day (2,049 h/yr), of which 86% is traditional TV, 7% is 

time-shifted TV, 3% is DVD/Blu-Ray, and 4% is video game console usage. These per-person usage 

figures remain relatively unchanged in recent years (5.5 h/day in 2012 and 2011). 

Of the TVs represented in our survey, Plasma TVs had the highest usage at about 5.8 h/day, followed by 

LCD (4.8), Projection (4.7), and CRT (3.1). Newer TVs had higher usage than TVs that were 3 or more 

years old (5.3 vs. 4.7 h/day), and larger TVs had higher usage than those less than 40 inches (6.1 vs. 4.4 

h/day). 

3.12.1.2.3 Unit Energy Consumption

To calculate UEC and AEC for TVs, we combined input from the CE Usage Survey with the power draw 

regressions from Table 3-71 to determine energy usage by mode for each TV usage group, subdivided by 

display technology and screen size. We then applied our 2013 installed base estimate of 300.7 million 

TVs to obtain the AEC estimates shown in Table 3-72. We estimate average unit energy consumption at 

166 kWh/yr in 2013 and about 9% lower than in 2010. Even though screen sizes of newly purchased TVs 

continue to increase, per-unit consumption has continued to drop stemming from the major fall of lessefficient CRT displays. 

Table 3-72: UEC and AEC calculations for TVs for 2013.

Usage Installed Base Usage Size Age Power [W] UEC AEC AEC

Group [millions] [%] [h/day] [in] [yr] Active Off [kWh/yr] [TWh/yr] Fraction

TV1 115 38% 7.0 41 4.4 105 1.1 274 31.6 63%

TV2 81 27% 3.8 32 5.6 81 1.6 125 10.1 20%

TV3 48 16% 2.6 29 6.0 78 1.9 89 4.2 9%

TV4 24 8% 2.4 29 6.5 80 2.0 84 2.0 4%

TV5 11 3% 1.6 28 7.3 81 2.4 65 0.7 1%

TV6+ 23 8% 1.1 28 8.0 84 2.6 57 1.3 3%

Total/Avg. 301 100% 4.4 34 5.5 90 1.6 166 50 100%

Estimates based on CE Usage Survey (Nov. 2013), CEA 2013 sales data, CEA partner surveys, and EPA power data.

Figure 3-49: TV unit energy consumption by usage priority and display type.

0

100

200

300

400

TV1 TV2 TV3 TV4 TV5 TV6+

off

on

kWh/yr

0

100

200

300

400

LCD Plasma CRT Proj.

off

on

kWh/yr
Fraunhofer USA Center for Sustainable Energy Systems 95

3.12.1.3 Annual Energy Consumption

We estimate that TVs consume 50 TWh/yr, with primary TVs responsible for 63% of the total AEC, as 

summarized in Table 3-72 and Table 3-73. This 23% decline from 2010 consumption comes primarily 

from the 15% drop in the installed base and from the massive decline of CRTs in favor of more efficient 

LCD displays.

About 93% of TV energy usage occurs in active mode, while the remaining 7% occurs in off mode. The 

shift toward lower off-mode consumption is a result of improved off-mode efficiency of newer TVs (the 

large majority under 1 W) and the concurrent retirement of older, unused TVs with higher off-mode 

power draw. Naturally a TV’s usage priority has the biggest influence: 98% of TV1 energy usage is from 

active mode, compared to less than 70% for TV5 and beyond.

Figure 3-50: Active and off mode AEC by TV priority and display type.

3.12.2 Comparison with Prior Energy Consumption Estimates

Prior estimates of television AEC are given in Table 3-73 together with our estimates of 50 TWh for 

2013. For the first time in over a decade, the number of plugged-in TVs has decreased significantly, with 

a shift from CRT to LCD TVs contributing to a sharp 20% decline in AEC. Our best understanding of this 

decline is that older, less-efficient TVs and primarily CRT displays are being taken out of service – either 

to be recycled, disposed of, or set aside. Since our only indication of these changes come from our 

phone survey, there remains some uncertainty. Active TV usage remained fairly consistent, while TV ontime has increased somewhat from previous estimates. Active mode power has continued to decrease, 

even while average screen size continues to increase, owing to the greater efficiency of newer displays. 

Table 3-73: Prior energy consumption estimates for TVs.

Year Units Power [W] Usage [h/yr] UEC AEC Source [millions] Active Off Active Off [kWh/yr] [TWh/yr]

2013 301 90 1.6 1,606 7,154 166 50 Current

2010 353 104 3.0 1,392 7,368 183 65 FhCSE 2011

2009 342 105 3.3 1,392 7,368 188 64 FhCSE 2011

2006 275 111 4.0 1,882 6,878 244 67 TIAX 2008

2006*237 98 4.0 1,882 6,878 222 53 TIAX 2007

2004*234 100 3.9 1,278 7,483 156 37 NRDC 2005

1998*212 75 4.5 1,443 7,317 150 31 LBNL 1999

1997*229 60 4.0 1,460 7,300 117 27 ADL 1998

1995*191 77 4.0 1,498 7,262 141 26 LBNL 1998

* Analog TVs only.

0

10

20

30

40

TV1 TV2 TV3 TV4 TV5 TV6+

off

on

TWh/yr

0

10

20

30

40

LCD Plasma CRT Proj.

off

on

TWh/yr
Fraunhofer USA Center for Sustainable Energy Systems 96

Older CRTs continue to be replaced with newer, more efficient digital flat panel TVs, as indicated by 

Figure 3-51 and Figure 3-52. About 91% of the 40 million TVs sold per year are flat panel LCD displays, 

and these have overtaken CRTs as the most prevalent display technology in homes. 

Figure 3-51: Annual TV sales to dealers by display technology (CEA 2013, 2010).

Figure 3-52: Cumulative TV sales to dealers by display technology since 1999 (CEA 2013, 2010).

3.12.3 References

ADL. 1998. “Electricity consumption by small end uses in residential buildings.” Final Report by Arthur D. 

Little for the U.S. Department of Energy, Office of Building Equipment. Aug. 

CEA. 2014. “2014 CRT Television and Monitors per U.S. Household”. CEA Market Research Report. April.

CEA. 2013. Second Annual Report of the eCycling Leadership Initiative. Consumer Electronics 

Association. http://www.ce.org/CorporateSite/media/Government-Media/Green/eCyclingLeadership-Initiative-Year-Two-Report.pdf. Apr. 

CEA O&M. 2009. “11th Annual Household CE Ownership and Market Potential.” CEA Market Research 

Report. Consumer Electronics Association. May.

CEA O&M. 2010. “12th Annual Household CE Ownership and Market Potential.” CEA Market Research 

Report. Consumer Electronics Association. May.

CEA S&F. 2013. “U.S. Consumer Electronics Sales & Forecasts 2009-2014.” CEA Market Research Report. 

Consumer Electronics Association. Jul.

CEA S&F. 2010. “U.S. Consumer Electronics Sales & Forecasts 2006-2011.” CEA Market Research Report. 

Consumer Electronics Association. Jul.

CEC. 2013. Appliance Efficiency Database. California Energy Commission. 

http://www.appliances.energy.ca.gov/QuickSearch.aspx. Retrieved Dec. 2013.

0

10

20

30

40

1999 2001 2003 2005 2007 2009 2011 2013

Projection

Plasma

LCD

CRT

TVs sold annually [millions]

0%

20%

40%

60%

80%

100%

1999 2001 2003 2005 2007 2009 2011 2013

Portion of annual sales

0

100

200

300

400

1999 2001 2003 2005 2007 2009 2011 2013

Projection

Plasma

LCD

CRT

TVs sold since 1999 [millions]

0%

20%

40%

60%

80%

100%

1999 2001 2003 2005 2007 2009 2011 2013

Portion of units sold since 1999
Fraunhofer USA Center for Sustainable Energy Systems 97

DOE. 2012. “Television Usage Analysis: Energy Efficiency Program for Consumer Products: Television 

Sets.” U.S. Department of Energy. http://www1.eere.energy.gov/buildings/appliance_standards/ 

pdfs/tv_tpnopr_usageanalysis.pdf. Mar.

EIA. 2011. “2009 Residential Energy Consumption Survey.” U.S. Energy Information Administration. 

http://www.eia.gov/consumption/residential/index.cfm. 

EPA. 2013. “ENERGY STAR program requirements for televisions.” Partner commitments Versions 4.0 

and 5.0. Environmental Protection Agency. Oct.

EPA. 2012, 2011, and 2010. ENERGY STAR Unit Shipment and Market Penetration Report. Calendar Year 

Summaries. Environmental Protection Agency. 

EPA. 2011. “Electronics Waste Management in the United States Through 2009.” Environmental 

Protection Agency. May

FhCSE. Urban, Bryan, Kurt Roth, and Verena Tiefenbeck. 2011. “Energy Consumption of Consumer 

Electronics in U.S. Homes in 2010.” Final Report to the Consumer Electronics Association. 

http://www.ce.org/CorporateSite/media/Government-Media/Green/Energy-Consumption-of-CE-inU-S-Homes-in-2010.pdf. Dec.

FhCSE. Roth, Kurt and Bryan Urban. 2009. “Assessments of the energy savings potential of policies and 

measures to reduce television energy consumption.” Final report to the Consumer Electronics 

Association. Oct.

LBNL. Rosen, K. and A. Meier. 1999. “Energy use of televisions and videocassette recorders in the U.S.” 

Lawrence Berkeley National Laboratory. Report LBNL-42393. Mar.

LBNL. Sanchez, M.C., J.G. Koomey, M.M. Moezzi, and W. Huber. 1998. “Miscellaneous electricity use in 

the U.S. residential sector.” Lawrence Berkeley National Laboratory. Report LBNL-40295. 

Nielsen. 2010. “Television audience 2009.” Apr. http://blog.nielsen.com/nielsenwire/wpcontent/uploads/2010/04/TVA_2009-for-Wire.pdf. 

Nielsen. 2012. Viewing on Demand. The Cross-Platform Report Q2: 2012. http://www.nielsen.com/ 

us/en/reports/2012/state-of-the-media--cross-platform-report-q2-2012.html. Nov. 

Nielsen. 2013. “No TV? 5 million U.S. households bid boob tube goodbye.” USA Today. 

http://www.usatoday.com/story/money/business/2013/04/07/zero-tv-homes/2061127. 

Nielsen. 2013. State of the Media U.S. Consumer Usage Report. 

Nielsen. 2013. Viewing on Demand. The Cross-Platform Report Q2: 2013. 

http://www.nielsen.com/us/en/reports/2013/q2-2013-cross-platform-report.html. Sept. 

NRDC. Horowitz, N. 2012. NRDC Comments on ENERGY STAR’s Final Draft Version 6.0 Eligibility Criteria 

for Televisions. National Research Defense Council. Jul. 

NRDC. Ostendorp, P., S. Foster, and C. Calwell. 2005. “Televisions: active mode energy use, new horizons 

for energy efficiency.” National Research Defense Council. Mar. 

TIAX. Roth, K., K. McKenny. 2007. “Energy consumption by consumer electronics in U.S. Residences.” 

Final report to the Consumer Electronics Association (CEA). Jan. 

TIAX. Roth, K., K. McKenny, R. Ponoum, and C. Paetsch. 2008. “Residential miscellaneous electric loads: 

energy consumption characterization and savings potential in 2006 and scenario-based projections 

for 2020.” Apr.
Fraunhofer USA Center for Sustainable Energy Systems 98

3.13 Video Game Systems

3.13.1 Current Energy Consumption

The video game systems described in this section refer to video game consoles, such as the Sony 

PlayStation 3, Nintendo Wii, or Microsoft Xbox 360, and includes consoles in the installed base as of Jul. 

2013. Hence, the Sony PlayStation 4 and Xbox One gaming consoles were not included as they were 

released in fall of 2013. Handheld devices, such as the Sony Playstation Portable and the Nintendo DS 

are not covered in this report. 

3.13.1.1 Installed Base

We estimate an installed base of 12836 million video game consoles in 2013 (see Table 3-74) based on 

the CE Usage Survey (see Appendix A). This is 17 percent higher than in 2010 (FhCSE 2011). We also 

asked in this survey about the ownership of recently released video game consoles such as Xbox One 

and PlayStation 4; however, the 128 million installed base estimate excludes those consoles. Appendix 

B.3.1 presents an installed base estimate for video game consoles in early 2014 that includes the Xbox 

One and PlayStation 4.

Table 3-74: Installed base of video game consoles.

Installed Base 

[millions] Penetration Sources

128 51% 2013 CE Usage Survey 

We estimate the installed base of different video game console models from the CE Usage Survey. Each 

video game console model has several vintages, defined by the year of release, that have different 

power draws in operational modes. Consequently, we estimate the installed base distribution by model 

and vintage using sales data provided by Microsoft, Nintendo and Sony (Calland 2014, Jessop 2014, 

Boxleitner 2014, Nintendo 2013). If the sum of the sales of a particular video game console model 

exceeds the installed-base estimate from the CE Usage Survey , we adjusted the installed base estimates 

for different vintages of specific models by eliminating units of the oldest vintage(s) until the installed 

based estimates agreed. For example, the survey yielded a lower installed base estimate of Microsoft 

Xbox 360 units than cumulative Xbox 360 sales, so we removed units sold in 2005 and 2006 from the 

installed base. We also found that all owners of the Nintendo GameCube console had not used the 

console for any purpose “yesterday” (see Figure 3-54). Thus, we assumed that no more units remained 

in the installed base. 

Figure 3-53 shows that so-called 7th generation consoles, i.e. the Nintendo Wii (Wii), Sony PlayStation 3

(PS3), and Microsoft Xbox360 (Xbox 360), account for 77% of the installed base. The Sony PlayStation 2 

(PS2), released in March, 2000, remains one of the most popular (17% of installed base) video game 

consoles (Figure 3-53); this is consistent with the 20% estimate in 2012 of Nielsen (2012). The Nintendo 

Wii U, released in Nov. 2012, introduced the 8th generation of video game consoles. As of mid-2013, we 

estimate that it accounted for approximately 1% of the installed base. 

 

36 We adjusted final installed base results using sales data provided by Nintendo, Sony and Microsoft (Calland 2014, Jessop 2014, Boxleitner 

2014, Nintendo 2013).
Fraunhofer USA Center for Sustainable Energy Systems 99

Figure 3-53: Fraction of video game systems installed in U.S. homes by platform.

3.13.1.2 Unit Energy Consumption

We used several modes to characterize gaming system energy consumption. Collectively, we refer to 

“Active-Gaming”, “Active-Video streaming”, and “Active-Video playback” as active modes. 

 Active – Gaming: The system is on and a game is being played.

 Active – Video streaming: The system is on and video or audio is being played from a 

network. 

 Active - Video playback: The system is on and video or audio is being played using its builtin DVD/Blu-ray drive. 

 Navigation: The console is on, but the user is not providing input to the console via the 

controller, i.e., the console is not being actively used. 

 Standby: The power has been switched off by the user, but the system remains plugged in.

The number of video game console owners who use consoles for video streaming is increasing (Nielsen 

2013), so our assessment considers separate modes for “Video streaming” and “Video playback.” The 

energy consumption characteristics of “Navigation” mode used in our previous study (FhCSE 2011) are

very similar to those of the “Idle” mode as defined in Hittinger et al. (2012) and in EPA’s specification for 

game consoles (EPA 2013). Consistent with our prior study, we decided to use only the “Navigation” 

mode in this study.

3.13.1.3 Power Draw

Table 3-75 summarizes the estimated power draw of video game consoles as a function of console 

platform, vintage, and operational mode. The power draw values for the 7th and 8th generations of video 

game consoles presented in this table were provided by video game console manufacturers (Calland 

2014, Jessop 2014, Boxleitner 2014). They are consistent with power draw measurements from other 

studies analyzing video game console energy consumption (LBNL 2013, Hittinger et al. 2012, NRDC 

2010). In addition, we used the power draw values for the Microsoft Xbox and Sony PlayStation 2 from 

NRDC (2010).

Wii U

1%

Wii

33%

Xbox 

360

26%

Xbox

5%

PS 3

18%

PS 2

17%
Fraunhofer USA Center for Sustainable Energy Systems 100

Table 3-75: Installed base and power draw by mode of video game systems.

Installed Base Power [W]

Years [millions] [%] Gaming Video 

Streaming

Video 

Playback Navigation Standby

Nintendo

Wii U 2012-2013 1.6 1.2% 33 31 - 32 0.4

Wii 2006-2013 42 33% 16 16 - 14 5.8 *

Microsoft

Xbox 360 S/E 2010-2013 21 17% 86 67 67 67 0.4

Xbox 360 2007-2009 12 9% 121 97 96 97 1.8

ALL Xbox 360/Wt. Avg. 2007-2013 33 26% 99 78 77 77 0.9

Xbox 2001-2008 6.1 5% 64 - - 60 1.7

Sony

PS3 Super Slim 2012-2013 4.3 3% 82 62 74 68 0.2

PS3 Slim 2009-2011 12 9% 102 77 94 91 0.7

PS3 2008 4.4 3% 137 112 126 115 1.3

PS3 2007 2.3 2% 190 160 178 165 1.4

PS3 2006 0.6 0.5% 220 166 209 188 1.5

ALL PS3/Wt. Avg. 2006-2008 23 18% 117 92 108 101 0.8

PS2 2000-2013 22 17% 24 24** 24 24 1.7

Total/Wt. Avg. - 128 100% 60 49 72 51 2.6

* Calculated as the weighted average based on the portion of different vintages of the Nintendo Wii gaming consoles by year (1.7, 1.7 and 

0.7 watts if connect24 disabled, 10, 7 and 5watts if enabled for Wii gaming consoles released since 2006, 2009 and 2010, respectively 

(Boxleitner 2014)) and assuming that 30% of users have the Wii connect24 disabled (FhCSE 2011). Wiiconnect24 is not available on the 

newer Wii U console.

** We used power draws for video streaming and playback the same as for active mode and navigation because we did not find power draw 

values for these modes. 

3.13.1.3.1 Usage

We asked about video game console usage in the CE Usage Survey (2013). Based on the responses 

received and our usage estimation models (see Appendix B.3.4 for more details), we estimate that 

systems spend an average of 1 hour total per day in all active modes, i.e., in active-gaming, active-video 

streaming and active-video playback modes. In addition, we estimate that video game consoles were left 

on for an additional 2.4 hours/day in 2013 (i.e., navigation mode). Among different video game console 

platforms, the most actively used video game consoles were the Xbox 360, PlayStation 3 and Wii U, for 

1.5, 1.5 and 1.1 hours/day, respectively (see Figure 3-54). Our estimates of average active usage and 

time spent in navigation mode in 2013 are less than the 3.1 hours/day active usage and 4.0 hours/day in 

on mode found in our study in 2010 (FhCSE 2011). 
Fraunhofer USA Center for Sustainable Energy Systems 101

Figure 3-54: Turned ON and actively used hours/day for different video game console platforms.

Table 3-76: Usage by different video game consoles (CE Usage Survey).

Usage [h/yr]

Years Gaming Video Streaming Video Playback Navigation Standby

Nintendo

Wii U 2012-2013 108 293 - 1,205 7,154

Wii 2006-2013 100 82 - 876 7,702

Microsoft

Xbox 360 S/Ea2008-2013 365 146 37 693 7,519

Xbox 360 2007 402 146 - 693 7,519

Xbox 2001-2008 183 - -

b

2,154 6,424

Sony

PS3 Slim & Super Slim 2006-2013 394 115 44 657 7,550

PS2 2000-2013 197 - 22 1,059 7,483

Total/Wt. Avg. - 245 89 21 885 7,521

a Xbox 360 S and Xbox 360 E are two redesigned model released in 2010 and 2013, respectively, of the Xbox 360 video game console 

(released in 2005).

b The Xbox has an accessory that enables the playing of DVDs. Eight percent of CE Usage Survey (2013) respondents reported that they 

played DVDs on their Xbox “yesterday” (See AppendixB.3). However, we did not use this data in our usage and energy consumption 

estimates because we did not have power draw data for Xbox gaming consoles using this accessory.

Table 3-77: Annual hours by mode for video game consoles for LBNL 2013, FhCSE 2011 and current study.

Year Active Modes Standby Source

2013 1,240 7,521 Current study

2013 1,704 7,070 LBNL 2013

2010 1,450 7,310 ResCE 2010

Table 3-78 compares the breakdown of console usage between gaming and other active modes in 2013, 

2012 and 2010. We found a similar breakdown of time spend in active modes in 2013 and 2010. 

According to Nielsen (2013), game console users spent about 8% less of their total active time gaming in 

2012 than in 2011.

Table 3-78: Comparison of different estimates for the portion of active time in gaming and other modes.

Year Active:Gaming Active:Other Source

2013 69% 31% Current study

2012 54% 46% Nielsen Newswire 2013

2010 66% 34% CEA Gaming and Energy Study 2010

0

1

2

3

4

5

6

7

Xbox Wii U PS2 Xbox

360 PS3 Wii

Left ON 5.9 3.3 2.9 1.9 1.8 2.4

Actively used 0.5 1.1 0.6 1.5 1.5 0.5

Hours
Fraunhofer USA Center for Sustainable Energy Systems 102

The CE Usage Survey found that the Nintendo Wii and Wii U gaming consoles were used more than 50% 

of the time for other purposes than gaming (Figure 3-55).

Figure 3-55: Distribution of active usage among gaming and video (streaming and playback) by platform.

3.13.1.3.2 Unit Energy Consumption

Our calculations of video game console UECs for different platforms are summarized in Table 3-79.

Table 3-79: UEC calculation for video game systems.

UEC [kWh/yr]

Years Installed Base

[millions] Gaming Video Streaming

Video 

Playback Navigation Standby Total

Nintendo

Wii U 2012-2013 1.6 3.5 9.2 - 39 2.6 54

Wii 2006-2013 42 1.6 1.3 - 13 45 60

Microsoft

Xbox 360 S/E 2010-2013 21 32 9.5 2.6 46 2.9 93

Xbox 360 2007-2009 12 45 14 2.9 67 14 143

ALL Xbox 360/Wt. Avg. 2007-2013 33 36 11 2.7 53 6.3 109

Xbox 2001-2008 6.1 12 - - 129 11 152

Sony

PS3 Super Slim 2012-2013 4.3 32 7.1 3.3 45 1.7 89

PS3 Slim 2009-2011 12 40 8.9 4.1 60 5.1 118

PS3 2008 4.4 54 13 5.5 76 9.8 158

PS3 2007 2.3 75 18 7.8 108 11 220

PS3 2006 0.6 87 19 9.2 124 11 250

ALL PS3/Wt. Avg. 2006-2008 23 46 11 4.7 66 6.1 134

PS2 2000-2013 22 4.7 - 0.5 25 13 43

Total/Wt. Avg. - 128 20 5.3 2.7 41 20 88

Figure 3-56 shows the breakdown of UEC and annual hours in 2013 by different modes compared with 

usage. On average, navigation mode accounts for the largest portion of UEC in 2013. 

Figure 3-56: Video game console UEC and usage by mode.

0%

20%

40%

60%

80%

100%

Xbox Xbox 360 PS2 PS3 Wii WiiU

Active-Video playback

Active-Video streaming

Active-Gaming

0% 20% 40% 60% 80% 100%

UEC

Usage

Active-gaming Video streaming Video playback Navigation Standby
Fraunhofer USA Center for Sustainable Energy Systems 103

3.13.1.4 Annual Energy Consumption

Video game systems consumed 11TWh in 2013 (see Table 3-80). 

Table 3-80: AEC summary for video game systems

UEC 

[kWh/yr]

Installed Base 

[million]

AEC 

[TWh]

88 128 11

Seventh-generation consoles, e.g. Microsoft Xbox 360, Nintendo Wii and Sony PlayStation 3, account for 

the largest portion of AEC (Figure 3-57) as well as the installed base.

Figure 3-57: Annual Energy Consumption by different video game consoles

3.13.2 Comparison with Prior Energy Consumption Estimates

Table 3-81 summarizes prior energy consumption estimates for video game systems.

Table 3-81: Prior energy consumption estimates for video game systems.

Year Units

[millions]

Power [W] Usage [h/yr]

Source Active

All

Idle +

Navigation Standby ActiveAll

Idle +

Navigation Standby UEC[kWh/yr]

AEC

[TWh/yr]

2013 128 58a51 2.6 355 885 7,521 88 11 Current

2013 105 46 - 1 1,704c- 7,056 68 7.1 LBNL 2013

2010 75 93d79 3.4 382 2,514e5,865 213 16 Hittinger et al. 2012

2010 109 85a75 2 1,120 330 7,310 135 14.7 FhCSE 2011

2008 63 - - - - - - - 16.3bNRDC 2008

2006 64 36 31 0.8 406 558 7,796 36 2.4 TIAX 2007

1999 54 8 - 1 175 - 8,585 10 0.5 LBNL 2001

1995 64 20 - 2 365 - 8,395 24 1.5 LBNL 1998

a Weighted average of gaming and other uses.

b Assumes that 50% of users leave on their system all the time.

c Includes time console is actively used and time console spends in navigation mode.

d Does not include power draw for Sony PlayStation 2.

e Assumed that 30% of users leave their console idle when not in use.

All three components of the AEC calculations have changed appreciably since 2010. First, the installed 

base increased by 17 percent. Relative to LBNL (2013), the current study found a higher proportion of 

PS2 consoles and fewer PS3 consoles; this could reflect differences due to the sample (households 

undergoing energy audits) and sample size (n=113) of that study (2013). 

Second, the average power draw in all modes decreased for the more recent versions of the 7th-

generation game consoles, which account for 77% of the installed base (Figure 3-58). In general, game 

console active gaming-mode power draw increased until it peaked around 2005/2006. Since then, the 

original versions of the two consoles with the highest active-mode power draw, the PS3 and Xbox 360, 

have been replaced by versions that, ultimately, drew about 65 and 52 percent less power than their 

original versions, respectively. On the other hand, the active-gaming mode power draw of the new Wii U 

Wii U

0.1

Nintendo Wii

2.5

Microsoft Xbox 360

3.4

Microsoft Xbox

0.9

Sony PS 3 

3.1

Sony PS 2

0.9

0 2 4 6 8 10 TWh/year 12
Fraunhofer USA Center for Sustainable Energy Systems 104

console is higher than that of the Wii it replaced. Nonetheless, the Nintendo Wii U still draws less power 

than the other two video game console platforms, and only accounts for about 1 percent of the 2013 

installed base. 

Figure 3-58: Historical active-gaming mode power draw values for video game systems (Calland 2014, Jessop 2014, Boxleitner 

2014, NRDC 2010)

Lastly, the estimated annual total active hours is almost three times smaller than in 2010, while the total 

number of active-all plus navigation hours decreased by about 18 percent (FhCSE 2011). The reason for 

the large decrease in estimated active-use hours is not clear. First, the active-all hours estimate is similar 

to the estimate derived in Hittinger et al. (2012) from Nielsen usage data for 2010 and that of another 

phone survey (5.8 hours/week per respondent; PWC 2012). The difference in active-all estimates 

between our current and prior study (FhCSE 2011) could be due to several reasons. First, in the 2013 

survey we asked about the respondent's usage "yesterday" instead of "per week" as in 2010. Asking 

about active weekly usage instead of one particular day (i.e. yesterday) could create biases in average 

active usage estimates because U.S. adults may not accurately recollect their weekly usage. Second, in 

2013, we asked for a response in hours and minutes, which can give a more granular answer than asking 

about "only hours”, which was survey method in 2010. Moreover, we found that our estimate (2.7 

hours/day) for active usage in 2013 excluding U.S. adults who answered zero hours/day is close to the 

2010 estimate (3.1 hours/day) including U.S. adults who answered zero hours/week. This suggests that 

in 2013 more U.S. adults answered that they did not use their video gaming console at all than in 2010. 

Potential explanations for a reduction in the total time spent in all active modes include the migration of 

some gaming activity to portable devices (i.e., smart phones and tablets) and higher penetration of 

video game consoles with auto power down (APD) functionality. 

The field-metering study performed by Lawrence Berkeley National Laboratory (LBNL 2013) monitored 

the power draw of 113 game consoles for three to ten weeks. The study measured an average time in all 

active modes that exceeds our estimate by more than 40 percent. This is mainly due to large differences 

in usage for the Wii consoles, i.e., LBNL (2013) estimates that the average Wii console spent more than 

four times more time in all active modes than non-Wii consoles. The reason for the difference in Wii 

0

50

100

150

200

250

2000 2002 2004 2006 2008 2010 2012 2014

Year of Release

PS3

PS3 Slim

PS2

PS3 Super Slim

Game Cube

Wii U

Xbox

Xbox 360

Xbox 360 Slim

Wii

PS 4

Xbox One

W
Fraunhofer USA Center for Sustainable Energy Systems 105

usage is not clear; however, both studies estimated similar time spent in active mode for the PS3 and 

Xbox 360.

3.13.3 References 

Boxleitner, W. 2014. Personal Communication. Nintendo of America Inc. Feb.

Calland, T. 2014. Personal Communication. Microsoft. Feb.

CEA. 2013. “15ft Annual household CE Ownership and Market Potential.” CEA Market Research Report. 

Consumer Electronics Association. Apr.

EPA. 2013. “Game Console Version 1.0 Recognition Program.” Mar.

https://www.energystar.gov/products/specs/game_console_version_1_0_recognition_program_pd

FhCSE. Urban, Bryan, Kurt Roth, and Verena Tiefenbeck. 2011. “Energy Consumption of Consumer 

Electronics in U.S. Homes in 2010.” Final Report to the Consumer Electronics Association. 

http://www.ce.org/CorporateSite/media/Government-Media/Green/Energy-Consumption-of-CE-inU-S-Homes-in-2010.pdf. Dec.

Hittinger, E., K.A. Mullins, I. Azevedo. 2012. “Electricity consumption and energy savings potential of 

video game consoles in the United States.” Energy Efficiency. Mar.

Jessop, J. 2014. Personal Communication. Sony Computer Entertainment America. Feb.

LBNL. Desroches, L., J. Greenblatt, and S. Pratt. 2013. “Video game console usage and national energy 

consumption: Results from a field-metering study” Lawrence Berkeley National Laboratory Report. 

LBNL- 6251E. Jun.

Matthews, M. 2013. “U.S. video game hardware in 2012: Winners, losers and retirees.” Gamasutra. Jan.

http://www.gamasutra.com/view/news/184714/US_video_game_hardware_in_2012_Winners_loser

s_and_retirees.php

Nielsen Newswire 2013, “Play vs. stream: the modern gaming console.” Mar.

http://www.nielsen.com/us/en/newswire/2013/play-vs--stream--the-modern-gaming-console.html. 

Nielsen. 2012. “U.S. Gaming: A 360oView.” Feb. http://www.nielsen.com/us/en/newswire/2012/thelatest-trends-in-us-video-gaming.html

Nintendo. 2013. “Consolidated Sales Transition by Region.” Sept.

http://www.nintendo.co.jp/ir/library/historical_data/pdf/consolidated_sales_e1309.pdf

NRDC. 2008. “Lowering the Cost of Play: Improving the Energy Efficiency of Video Game Consoles.” Ecos 

Consulting. http://www.nrdc.org/energy/consoles/files/consoles.pdf.

PWC. 2012.”The Evolution of Video Gaming and Content Consumption”. PricewaterhouseCoopers LLP. 

http://www.pwc.com/us/en/industry/entertainment-media/publications/assets/pwc-video-gamingand-content-consumption.pdf .

Sony. 2010. “PS3 System Software Update v3.40 And PlayStation Plus Available Later Today.” 

http://blog.eu.playstation.com/2010/06/28/ps3-system-software-update-v3-40-and-playstationplus-available-later-today/.

Sony. 2012. “PS3 System Software Update (v4.20).” http://blog.us.playstation.com/2012/06/25/ps3-

system-software-update-v4-20/.
Fraunhofer USA Center for Sustainable Energy Systems 106

3.14 Other Devices

We estimate that other CE devices not analyzed in detail consumed about 28 TWh of electricity in 2013, 

an amount equal to 17 percent of total residential CE AEC. Table 3-82 through Table 3-87 and Figure 

3-59 summarize the AEC estimates and the data used to calculate the AEC of these products. In general, 

these estimates have a higher degree of uncertainty than the estimates for CE products analyzed in 

greater detail.

37 The “other” category in 2013 includes several products evaluated in depth in the 2010 

study that were not evaluated in further detail in this study. Typically such products had moderate or 

lower AECs in 2010, and our initial analysis suggested that their UEC was not likely to have changed 

greatly in 2013.

Table 3-82: UEC and installed base estimates for other products.

Product UEC 

[kWh/yr]

Installed Base 

[millions]

AEC 

[TWh]

AV Receiver with surround sound processor 65 48 3.1

Bluetooth Headset 5.4 67 0.4

Blu-ray player 14 52 0.7

Boombox 25 109 2.7

Camcorder 2.3 58 0.1

Copy machine (stand-alone) 14 9 0.1

Cordless phone 12 128 1.5

Digital camera 0.3 156 0.05

Digital picture frame 6.5 50 0.3

DVD Player 22 142 3.1

eReader 2.7 45 0.1

External Storage Device 17 89 1.5

Fax Machine (stand-alone) 46 10 0.5

Handheld GPS 1.3 79 0.1

Headphones 0.6 267 0.2

Home Theater in a Box (HTIB) 89 20 1.8

Internet Phone Device 36 60 2.2

Mobile (non-smart) Phone 2.2 121 0.3

Portable DVD or Blu-ray disc player 2.7 80 0.2

Portable Game Devices 4.1 61 0.3

Portable media/MP3 Player/CD Player 5.6a149 0.8

Portable Wireless Speaker 1.0 48 0.05

Printer + MFD (multi-functional device) 22 93 2.0

Projector 55 4 0.2

Radio 9.2 81 0.7

Scanner (stand-alone) 0.8 9 0.01

Soundbar 82 16 1.3

Telephone Answering Device 14 16 0.2

Video Cassette Recorder (VCR) 34 43 1.5

Total/Wt. Avg. 13 2,110 28

a UEC from Roth and McKenney (2007).

 

37 In addition, the uncertainty in the estimates for “other” products can vary significantly among products.
Fraunhofer USA Center for Sustainable Energy Systems 107

Figure 3-59: UEC, installed base, and AEC of other CE devices evaluated in less detail.

0.8

0.3

1.0

1.3

2.7

14

2.3

0.6

2.7

55

14

4.1

2.2

6.5

5.4

46

14

9.2

5.6

82

12

34

17

89

22

36

25

65

22

0 20 40 60 80 100

Scanner (stand-alone)

Digital camera

Portable Wireless Speakers

Handheld GPS

eReader

Copy machine (stand-alone)

Camcorder

Headphones

Portable DVD or Blu-ray disc player

Projector

Telephone Answering Device

Portable Game Devices

Mobile (non-smart) Phone

Digital picture frame

Bluetooth Headset

Facsimile Machine (stand-alone)

Blu-ray player

Radio

Portable media/MP3 Players/CD Players

Soundbar

Cordless phone

VCR

External Storage Device

Home Theater in a Box (HTIB)

Printer+MFD (multi-functional device)

Internet Phone Device

Boombox

AV Receiver with surround sound...

DVD Player

Unit Energy Consumption [kWh/yr]

9.0

156

48

79

45

9.0

58

267

80

4.0

16

61

121

50

67

10

52

81

149

38

16

128

43

89

20

93

60

109

48

142

0 100 200 300

Installed Base [millions]

0.01

0.0

0.05

0.1

0.1

0.1

0.1

0.2

0.2

0.2

0.2

0.3

0.3

0.3

0.4

0.5

0.7

0.7

0.8

1.1

1.3

1.5

1.5

1.5

1.8

2.0

2.2

2.7

3.1

3.1

0 1 2 3 4

Annual Energy Consumption [TWh]
108

Table 3-83: Average power draw by mode estimates for other products.

Product Power [W]

Active/Charging Sleep/Idle Standby/Off

AV Receiver with surround sound processor 52 2 1

Bluetooth Headset NA / 2.0a1.2 0.3

Blu-ray player 30 16 0.5

Boombox 5.2 4.1 2.1

Camcorder NA / 9.6 0.4 0.4

Copy machine (stand-alone) 9.6 NA 1.5

Cordless phone 1.9 NA 0.5

Digital camera NA / 4.0 NA 0.3

Digital picture frame 3.1 NA 0

DVD Player 10 0.6 0

eReader NA / 1.4a1.2 0.3

External Storage Device 1.2 NA NA

Fax Machine (stand-alone) 6.5 5.2 0.4

Handheld GPS NA / 1.4a1.2 0.3

Headphones NA / 2.4 a1.2 0.3

Home Theater in a Box (HTIB) 37 33 1.3

Internet Phone Device 6 4 NA

Mobile (non-smart) Phone 4 2.2 0.2

Portable DVD or Blu-ray disc player NA / 3.2a1.8 1.0

Portable Game Devices NA / 1.8a1.2 0.3

Portable media/MP3 Player/CD Player 5 3 1.7

Portable Wireless Speaker NA / 5.1a2.3 1.4

Printer+MFD (multi-functional device) 28 4 2.4

Projector 182 10 4.6

Radio 4.3 NA 1.6

Scanner (stand-alone) 10 NA 1.5

Soundbar 30b12 b4.0 b

Telephone Answering Device 2 NA NA

Video Cassette Recorder (VCR) 6.6 NA 1.2

a Power draw for charging is estimated from the battery energy capacity [Wh] of a battery charger divided by charging

efficiency and charge time [hours] (DOE 2012a, DOE 2012b). DOE did not provide the charger efficiency for some consumer 

electronics devices (DOE 2012b); therefore, we used the average charger efficiency of the devices from the same classes 

defined in DOE (2012a). For example, for Handheld GPS and Headphones we used Mobile Phone charging efficiency, for 

Portable Wireless Speakers we used Computer Speaker charging efficiency, and for eReaders we used Tablet charging

efficiency.

b Because the basic functionality and total system output power of soundbar systems are similar to those of mini shelf stereo 

systems, we assumed that soundbars have the same power draw values as Mini Shelf Stereo System.
109

Table 3-84: References for power draw by mode estimates for other products

Product Sources

AV Receiver with surround sound processor FhCSE (2011)

Bluetooth Headset DOE (2012a), DOE (2012b)

Blu-ray player FhCSE (2011)

Boombox Bensch et al. (2010), Fraunhofer Measurements 2014

Camcorder McAllister and Farrell (2004)

Copy machine (stand-alone) LBNL (2008)

Cordless phone Bensch et al. (2010)

Digital camera McAllister and Farrell (2004), Foster Porter et al. (2006), Wood (2011)

Digital picture frame Bensch et al. (2010)

DVD Player LBNL (2013)

eReader DOE (2012a), DOE (2012b)

External Storage Device Bensch et al. (2010)

Fax Machine (stand-alone) Bensch et al. (2010)

Handheld GPS DOE (2012a), DOE (2012b)

Wireless Headphone DOE (2012a), DOE (2012b)

Home Theater in a Box (HTIB) Roth and McKenney (2007)

Internet Phone Device YouSustain (2009), Ooma (2009), Roth et al. (2006)

Mobile (non-smart) Phone Bensch et al. (2010), LBNL (2008)

Portable DVD or Blu-ray disc player DOE (2012a), DOE (2012b)

Portable Game Device DOE (2012a), DOE (2012b)

Portable media/MP3 Player/CD Player Bensch et al. (2010), SELINA (2010)

Portable Wireless Speaker DOE (2012a), DOE (2012b)

Printer+MFD (multi-functional device) FhCSE (2011)

Projector Meister et al. (2011)

Radio Bensch et al. (2010)

Scanner (stand-alone) Bensch et al. (2010)

Soundbar FhCSE (2013)

Telephone Answering Device Bensch et al. (2010)

Video Cassette Recorder (VCR) Bensch et al. (2010)
110

Table 3-85: Annual usage by mode estimates for other products.

Product Active/Charging Sleep/Idle Standby/Off

AV Receiver with surround sound processor 950 7,610 200

Bluetooth Headset 314 b3,217 c0

d

/4,015e

Blu-ray player 300 30 8,430

Boombox 1,971 NA 6,789

Camcorder NA NA NA

Copy machine (stand-alone) 50aNA 8,710 a

Cordless phone 7,044 NA 1,716

Digital camera 13 NA 8,752

Digital picture frame 4,781 NA 3,979

DVD Player 2,044 1,861 4,855

eReader 526 b752 c548d/6,935 e

External Storage Device 8,760 NA NA

Fax Machine (stand-alone) 146 NA 8,614

Handheld GPS 73 b110c0

d

/8,578e

Headphone 146 b219 c0

d

/4,015e

Home Theater in a Box (HTIB) 1,580 730 6,450

Internet Phone Device 365 8,395 0

Mobile (non-smart) Phone 110 NA 8,650

Portable DVD or Blu-ray disc player 58 b1,402 c0

d

/7,300

e

Portable Game Devices 204 b2,738 c3,103d/2,920e

Portable media/MP3 Player/CD Player 657 NA 8,103

Portable Wireless Speaker 146 b219 c0

d

/4,015e

Printer+MFD (multi-functional device) 103 1,212 7,445

Projector 694 613 7,453

Radio 620 NA 8,140

Scanner (stand-alone) 146 NA 8,614

Soundbar 1,580f730 f6,450 f

Telephone Answering Device 8,760 NA NA

Video Cassette Recorder (VCR) 1,497 NA 7,263

a Notably high uncertainty for this value.

b Hours/year the device spends charging. Calculated as a product of charges/year and charge time (DOE 2012a).

c Hours/year the device spends in maintenance state, i.e. the device is fully charged but still connected to its charger (DOE 

2012a).

d Time in hours/year the device charger spends plugged into an electrical socket but without any device connected to it (“No 

Battery” in DOE spreadsheet 2012a).

e Time in hours/year the device charger spends unplugged (DOE 2012a).

f Usage in all operational modes for Soundbar is taken the same as for HTiB because of a similar usage pattern for these audio 

systems (see HTiB usage).
111

Table 3-86: References for annual usage by mode estimates for other products.

Product Sources

AV Receiver with surround sound processor FhCSE (2011)

Bluetooth Headset DOE (2012a), DOE (2012b)

Blu-ray player FhCSE (2011)

Boombox Bensch et al. (2010)

Camcorder NA

Copy machine (stand-alone) FhCSE (2011)

Cordless phone Bensch et al. (2010)

Digital camera Roth and McKenney(2007)

Digital picture frame Bensch et al. (2010)

DVD Player LBNL (2013)

eReader DOE (2012a), DOE (2012b)

External Storage Device Bensch et al. (2010)

Fax Machine (stand-alone) Bensch et al. (2010)

Handheld GPS DOE (2012a) , DOE (2012b)

Wireless Headphone DOE (2012a) , DOE (2012b)

Home Theater in a Box (HTIB) Roth and McKenney (2007)

Internet Phone Device Roth et al. (2006)

Mobile (non-smart) Phone Bensch et al. (2010)

Portable DVD or Blu-ray disc player DOE (2012a) , DOE (2012b)

Portable Game Devices DOE (2012a) , DOE (2012b)

Portable media/MP3 Player/CD Player Bensch et al. (2010) for CD players

Portable Wireless Speaker DOE (2012a) , DOE (2012b)

Printer+MFD (multi-functional device) FhCSE (2011)

Projector FhCSE (2011)

Radio Bensch et al. (2010)

Scanner (stand-alone) Bensch et al. (2010)

Soundbar Assumed the same as HTIB usage

Telephone Answering Device Bensch et al. (2010)

Video Cassette Recorder (VCR) Bensch et al. (2010)
112

Table 3-87: References for installed base estimates for other products.

Product Sources

AV Receiver with surround sound processor CEA (2013a)

Bluetooth Headset CEA (2013a)

Blu-ray player CEA (2013a)

Boombox Roth and McKenney (2007), CEA (2013b)

Camcorder CEA (2013a)

Copy machine (stand-alone) FhCSE (2011)

Cordless phone Scaled 2010 estimate (FhCSE 2011) based on ratio of landline 

subscriptions in 2010 and 2013 (Marketingcharts 2012, Axvoice 2012) 

Digital camera CEA (2013a)

Digital picture frame CEA (2010), CEA (2013b)

DVD Player CEA (2013a)

eReader CEA (2013a)

External Storage Device CEA (2013a)

Fax Machine (stand-alone) DOE/EIA RECS (2009)

Handheld GPS CEA (2013a)

Wireless Headphone CEA (2013a)

Home Theater in a Box (HTIB) Koenig (2013)

Internet Phone Device FCC (2011), CEA (2013b)

Mobile (non-smart) Phone CEA (2013a)

Portable DVD or Blu-ray disc player CEA (2013a)

Portable Game Device CEA (2013a)

Portable Headset Audio CEA (2010), CEA (2013b)

Portable media/MP3 Player/CD Player CEA (2013a)

Portable Wireless Speaker CEA (2013a)

Printer+MFD (multi-functional device) CEA (2013a)

Projector Extrapolated to U.S. from German data (Statistica 2011)

Radio Bensch et al. (2010)

Scanner (stand-alone) RASS (2009)

Soundbar CEA (2013a)

Telephone Answering Device DOE/EIA RECS (2009), CEA (2013b)

Video Cassette Recorder (VCR) Bensch et al. (2010), CEA (2013b)

3.14.1 References

Axvoice. 2012. “US telecom industry from 2010 to 2015.” May. http://blog.axvoice.com/us-telecomindustry-from-2010-to-2015-a-research-by-axvoice/ .

Bensch, I., S. Pigg, K. Koski and R. Belshe. 2010. “Electricity Savings Opportunities for Home Electronics 

and Other Plug-In Devices in Minnesota Homes – A technical and behavioral field assessment.” Final 

Report by the Energy Center of Wisconsin, ECW Report 257-1. May. 

http://www.state.mn.us/mn/externalDocs/Commerce/CARD_Plugging_into_Savings_Study_0527100

14507_MN_Home_Elect_Devices.pdf. 

CEA. 2010. “12th Annual household CE Ownership and Market Potential.” CEA Market Research Report. 

Consumer Electronics Association. May. 

CEA. 2013a. “15th Annual CE Ownership and Market Potential Study.” CEA Market Research Report, 

April, 2013. Consumer Electronics Association.

CEA. 2013b. “U.S. Consumer Electronics Sales & Forecasts 2009-2014.” CEA Market Research Report, 

July, 2013. Consumer Electronics Association. 

DOE. 2012a. “Rulemaking for Battery Chargers and External Power Supplies Energy Conservation 

Standard. Energy Use Analysis Spreadsheet.” Feb. 17, 2012.

http://www.regulations.gov/#!documentDetail;D=EERE-2008-BT-STD-0005-0084. 
113

DOE. 2012b. “Test Results for External Power Supply Energy Conservation Standards Preliminary 

Analysis. http://www.regulations.gov/#!documentDetail;D=EERE-2008-BT-STD-0005-0080. Apr.

DOE/EIA RECS. 2009. “Residential Energy Consumption Survey (RECS) – Computers & other electronics: 

Table HC5.1 Computers and Other Electronics in U.S. Homes, By Housing Unit Type, 2009.” 

http://www.eia.gov/consumption/residential/data/2009/#undefined.

FCC. 2011. “Local telephone competition: status as of Jun. 30, 2010.” Federal Communications 

Commission. Mar. http://hraunfoss.fcc.gov/edocs_public/attachmatch/DOC-305297A1.pdf. 

FhCSE. Urban, Bryan, Kurt Roth, and Verena Tiefenbeck. 2011. “Energy Consumption of Consumer 

Electronics in U.S. Homes in 2010.” Final Report to the Consumer Electronics Association. 

http://www.ce.org/CorporateSite/media/Government-Media/Green/Energy-Consumption-of-CE-inU-S-Homes-in-2010.pdf. Dec.

Foster Porter, S., L. Moorefield, P. May‐Ostendorp. 2006. “Final Field Research Report.” Final Field 

Research Report by Ecos Consulting to the California Energy Commission. 31 Oct.

Koenig, S. 2013. Personal Communication. Consumer Electronics Association, Director of Industry 

Analysis. Oct.

LBNL 2008. “Low-Power Mode Energy Consumption in California Homes.” Pier Final Project Report 

prepared by Lawrence Berkeley National Laboratory for California Energy Commission Public Interest 

Energy Research Program. Sept. http://www.energy.ca.gov/2008publications/CEC-500-2008-

035/CEC-500-2008-035.PDF. 

LBNL. 2013. “Field data collection of miscellaneous electrical loads in Northern California: initial results.” 

Lawrence Berkeley National Laboratory Final Report, LBNL-6115E. Jul.

Marketingcharts. 2012. “Landline Phone Penetration Dwindles as Cell-Only Households Grow.” Jul.

http://www.marketingcharts.com/wp/traditional/landline-phone-penetration-dwindles-as-cell-onlyhouseholds-grow-22577/.

McAllister, J. and A. Farrell. 2004. “Power in a Portable World: Usage Patterns and Efficiency 

Opportunities for Consumer Battery Chargers”, Proc. ACEEE Summer Study on Energy Efficiency in 

Buildings, 22-27 August, Pacific Grove, CA.

Meister, B.C., C. Scruton,V. Lew, L. ten Hope and M. Jones. 2011. “Office Plug Load Field Monitoring 

Report.” Final Field Project Report by Ecos Consulting to the California Energy Commission. Apr. 

http://www.energy.ca.gov/2011publications/CEC-500-2011-010/CEC-500-2011-010.pdf. 

RASS. 2009. “Massachusetts Residential Appliance Saturation Survey (RASS).” Prepared by Opinion 

Dynamics Corporation for Cape Light, National Grid, Nstar Electric Unitil, Western Massachusetts 

Electric Company. Apr. http://www.env.state.ma.us/dpu/docs/electric/09-64/12409nstrd2af.pdf. 

Roth, K. and K. McKenney. 2007. “Energy Consumption by Consuer Electronics (CE) in U.S. Residences.” 

Final Report by TIAX LLC to the Consumer Electronics Association (CEA). Dec. http://www.ce.org/pdf/ 

Energy%20Consumption%20by%20CE%20in%20U.S.%20Residences%20%28January%202007%29.pdf

Roth, K., R. Ponoum, and F. Goldstein. 2006. “U.S. Residential Information Technology Energy

Consumption in 2005 and 2010.” Final Report by TIAX LLC to the U.S. Department of Energy, Building 

Technology Program. Mar.

SELINA. 2010. “Standby and Off-mode Energy Losses In New Appliances Measured in Shops: 

Consumption Monitoring Campaign of Standby and Off-Mode Energy Losses in New Equipments.” 30 

Jun. http://www.selina-project.eu/files/ Measurements%20of%20standby%20energy%20losses 

%20in%20new%20equipment.pdf. 
114

Statistica. 2011. “Beamer, Projektoren im Haushalt: Anzahl der Personen, bei denen ein Beamer bzw. 

Projektor zur Darstellung von Fernseh- oder Computerbildern im Haushaltvorhanden ist, von 2008 bis 

2010 (in Millionen).” Available (in German) at: http://de.statista.com/statistik/daten/studie/169550/ 

umfrage/beamer-projektoren-im-haushalt/. 

Wood, R.W. 2011. Personal Communication. Eastman Kodak Company. Sept. 
115

4 Conclusions

We used a bottom-up approach to characterize U.S. residential consumer electronics (CE) energy 

consumption in 2013. Our effort focused on the 17 priority products listed in Table 4-1. In addition, we 

developed preliminary estimates for 29 other CE categories. For each CE category, we used a range of 

sources to develop estimates for the installed base and average power draw and annual usage by mode. 

Table 4-1: Consumer electronics analyzed in further detail.

Audio-Visual Equipment Computers & Peripherals

Home Audio

Speaker Dock

Compact Stereo System

Televisions

Video Game Consoles

Set Top Boxes

Cable

Standalone

Satellite

Telco

Desktop PC

Portable PC

Computer Speakers

Computer Monitor

Smart Phone

Tablet Computer 

Networking Equipment

Integrated Access Device 

Modem

Router

We estimate that residential CE consumed about 169TWh of electricity in 2013, an amount equal to 12% 

of residential electricity consumption and 8.4% of residential primary38 energy consumption, 

respectively (see Figure 4-1 and Figure 4-2; DOE/EIA 2014a,b, DOE 201239). For comparison, DOE (2012) 

estimates that “computers” and “electronics” accounted for just under 15 percent of residential 

electricity consumption in 2010.

Figure 4-1: Residential electricity consumption in 2013 by major end uses (DOE 2012, Current Study).

 

38 Residential primary energy is the total energy content of the fuel required to meet all end uses. Primary energy includes fuels consumed at 

the home, e.g., natural gas and oil for space and water heating, and fuel consumed at the power plant to generate electricity and to overcome 

transmission and distribution losses. On average, a power plant must consume an average of 3.1 kWh of primary energy to deliver 1kWh to a 

building (DOE 2012).

39 Breakdown of electricity consumption based on DOE 2012, percentage of residential primary energy consumption from DOE/EIA 2014a,b.

17%

2.9%

6.7%

8.8%

9.4%

9.6%

12%

12%

21%

0% 5% 10% 15% 20% 25%

Other (non-CE)

Cooking

Wet Cleaning

Space Heating

Refrigeration

Water Heating

Consumer Electronics

Lighting

Space Cooling

Percentage of Total Residential Electricity Consumption in 2013
116

Figure 4-2: Residential primary energy consumption in 2013 by major end uses (DOE 2012, Current Study).

As with the prior two residential CE energy consumption studies (Roth and McKenney 2007, FhCSE 

2011), three product categories accounted for a majority of residential CE AEC, televisions (30%), set-top 

boxes (18%), and computers (13%; see Figure 4-3). 

Figure 4-3: Residential CE electricity consumption by category.

13%

3.2%

4.9%

6.5%

8.4%

8.4%

13%

15%

28%

0% 5% 10% 15% 20% 25% 30%

Other (non-CE)

Cooking

Wet Cleaning

Refrigeration

Consumer Electronics

Lighting

Water Heating

Space Cooling

Space Heating

17%

0.4%

0.4%

1%

1%

2%

2%

2%

2%

3%

3%

3%

3%

6%

7%

9%

9%

30%

0% 10% 20% 30%

Other CE Devices

Tablet

Smart Phone

Speaker Dock

STB - Standalone

Computer Speaker

Modem

STB - Telco

Internet Access Device

Portable PC

Compact Stereo System

Router and other

Computer Monitor

STB - Satellite

Video Game Console

STB - Cable

Desktop PC

Television

Percentage of Total Residential CE Energy Consumption
117

The unit electricity consumption (UEC) of the categories studied in more detail varies greatly among 

categories (see Figure 4-4).

Figure 4-4: Unit electricity consumption for the CE categories evaluated in detail.

As in prior studies, active modes accounted for a large majority of residential CE AEC (70%; see Figure 

4-5), although the UEC breakdown by mode varied significantly among categories (see Figure 4-6).

Figure 4-5: AEC by operational mode for the categories evaluated in detail.

12

4.5

6.1

19

42

45

53

55

58

59

62

75

88

106

112

128

166

186

0 50 100 150 200

Other CE Devices

Smart Phone

Tablet

Speaker Dock

Computer Speaker

STB - Standalone

Portable PC

Modem

Computer Monitor

Router and other

Internet Access Device

Compact Stereo System

Video Game Console

STB - Telco

STB - Satellite

STB - Cable

Television

Desktop PC

Unit Energy Consumption [kWh/year]

Active

70%

Idle

12%

Sleep

11%

Off

7%
118

Figure 4-6: Breakdown of UEC by operational modes for the categories evaluated in detail.

4.1 Key Trends

Although the installed base of CE in homes increased to 3.8 billion devices in 2013 from 2.9 billion in 

2010, our estimate for residential CE electricity consumption is 12 percent lower than that for 2010 

(Urban et al. 2011). To a large extent, this decrease reflects a few key trends for televisions and 

computers; together, these two categories account for about 43 percent of residential CE AEC.

4.1.1 Televisions

Since the first evaluation of CE energy consumption (for 2006; Roth and McKenney 2007), televisions 

have always accounted for the largest portion of CE energy consumption. For the first time in over a 

decade, the number of plugged-in TVs has decreased significantly, with a shift from CRT to LCD TVs 

contributing to more than a 20% decline in their estimated AEC from 2010 to 2013. Around 90% of the 

40 million TVs sold per year are flat-panel LCD displays (CEA 2013b), and these have overtaken CRTs as 

the most prevalent display technology deployed in homes. Our best understanding of this installed base 

decrease of about 50 million TVs plugged in within the last month is that a large portion of older, lessefficient CRT displays have been removed from service. Since our only indication of this change come 

from our phone survey, there remains some uncertainty in its precise magnitude. 

Total active TV usage has remained fairly consistent over time, while per-TV on-time has increased 

somewhat from 2010. Active-mode power draw has continued to decrease (from an average of 104 W in 

2010 to 90 W), even while average screen size continues to increase (34 inches in 2013, up from 29 

0% 20% 40% 60% 80% 100%

Video Game Console

Speaker Dock

Computer Speaker

Desktop PC

STB - Satellite

Compact Stereo System

STB - Cable

STB - Telco

Smart Phone

Portable PC

STB - Standalone

Tablet

Computer Monitor

TVs

Internet Access Device

Router and other

Modem

Active Idle Sleep Off/Standby
119

inches in 2010 [Urban et al. 2011] and 26 inches in 2006 [Roth and McKenney [2007]), owing to the 

greater efficiency of newer displays. 

4.1.2 Computers

We evaluated three computer types as well as smart phones in more depth. Overall, the estimated total 

AEC of all computers has decreased by 25 percent since 2010. A migration of the installed base to much 

less energy-intensive tablet computers (i.e., about nine-fold less than portable; see Figure 4-4) and 

application of more refined methods to evaluate computer usage are the main drivers for this decrease. 

The plugged-in installed base of both desktop and portable computer decreased from 2010 to 2013 

(desktop: 101 to 88 million, portable: 132 to 93 million. We believe that this is due to the 25-fold 

increase in the ownership of tablets, from 4 million (Urban et al. 2011) to 100 million (CEA 2013a). 

Including tablet computers, the installed base of all computers categories in 2013 was 19 percent higher 

than in 2010. 

We also estimated lower annual hours spent in active mode for both desktop (13%) and portable (36%) 

computers in 2013 than in 2010. This primarily reflects refinements in the CE Usage Survey and models 

that we think improve the accuracy of our estimates for time in operational modes for desktop PCs. 

Specifically, the current approach increases the precision the survey questions posed by asking about 

three times of day (morning, afternoon, and evening). This provides a richer representation of usage 

throughout the whole day than in Urban et al. (2011). In addition, we think that breaking the day into 

more discrete time periods increases the accuracy of peoples’ responses for total computer usage.

One consequence of the decreased installed base of desktop and portable computers is a 27 percent 

decrease in the installed base of monitors. In addition, our estimate of active-mode usage (tied to the 

enhanced computer usage models described above) decreased by 36 percent. That, combined with a 

decrease in the average power draw in all modes (due to the rise of LED backlit monitors since 2010; 

DisplaySearch 2014) resulted in a 40 percent decrease in UEC. Taken all together, the estimated monitor 

AEC decreased by 54 percent.
120

References 

CEA. 2010a. “12th Annual household CE Ownership and Market Potential.” CEA Market Research 

Report. Consumer Electronics Association. May. 

CEA. 2010b. “U.S. Consumer Electronics Sales & Forecasts 2006-2011.” CEA Market Research Report. Jul.

CEA. 2013a. “15th Annual CE Ownership and Market Potential Study.” CEA Market Research Report, 

April, 2013. Consumer Electronics Association.

CEA. 2013b. “U.S. Consumer Electronics Sales & Forecasts 2009-2014.” CEA Market Research Report, 

July, 2013. Consumer Electronics Association.

DisplaySearch. 2014. “Quarterly Desktop Monitor Shipment and Forecast Report, 2011-13”.

DOE. 2012. “2011 Buildings Energy Data Book.” Prepared for the Building Technologies Program, Energy 

Efficiency and Renewable Energy, U.S. Department of Energy by D&R International, Ltd. Mar. 

DOE/EIA. 2014a. “Electric Power Monthly: Table 5.1. Retail Sales of Electricity to Ultimate Customers”. 

U.S. Department of Energy, Energy Information Administration. Feb. 21.

DOE/EIA. 2014b. Annual Energy Outlook 2014 Early Release: Energy Consumption by Sector and Source. 

U.S. Department of Energy, Energy Information Administration. Retrieved Mar. 6.

FhCSE. Urban, Bryan, Kurt Roth, and Verena Tiefenbeck. 2011. “Energy Consumption of Consumer 

Electronics in U.S. Homes in 2010.” Final Report to the Consumer Electronics Association. 

http://www.ce.org/CorporateSite/media/Government-Media/Green/Energy-Consumption-of-CE-inU-S-Homes-in-2010.pdf. Dec.

Kawamoto, K., J. Koomey, B. Nordman, R. Brown, M.A. Piette, M. Ting, and A. Meier. 2001. “Electricity 

used by office equipment and network equipment in the U.S.: Detailed report and appendices.”

Lawrence Berkeley National Laboratory Final Report, LBNL-45917. Feb.

Roth, K., F. Goldstein, and J. Kleinman. 2002. ”Energy Consumption by Office and Telecommunications 

Equipment in Commercial Buildings - Volume I: Energy Consumption Baseline.” Final Report by Arthur 

D. Little, Inc. to Office of Building Equipment (DOE). Jan.

Roth, K., R. Ponoum, F. Goldstein. 2006. “U.S. residential information technology energy consumption in 

2005 and 2010.” Final Report by TIAX LLC to the U.S. Department of Energy, Building Technology 

Program. Mar.

Roth, K. and K. McKenney. 2007. “Energy Consumption by Consuer Electronics (CE) in U.S. Residences.”

Final Report by TIAX LLC to the Consumer Electronics Association (CEA). Dec.

http://www.ce.org/pdf/Energy%20Consumption%20by%20CE%20in%20U.S.%20Residences%20%28J

anuary%202007%29.pdf. 

Roth, K., K. McKenney, R. Ponoum, and C. Paetsch. 2008. “Residential Miscellaneous Electric Loads: 

Energy Consumption Characterization and Savings Potential in 2006 and Scenario-based Projections 

for 2020.” Final Report by TIAX LLC to U.S. Department of Energy.
121

Appendix A – CE Usage Surveys

As part of this study, the CEA funded phone surveys that asked respondents questions about CE installed 

in their household and how they are used. The questions ultimately posed were developed by 

Fraunhofer CSE in close consultation with the CEA Market Research Team, which regularly performs 

surveys on a variety of topics. CEA is a member of the Marketing Research Association (MRA) and 

adheres to the MRA’s Code of Marketing Research Standards. The CEA employed the services of Opinion 

Research Corporation (ORC) to conduct telephone interviewing. The telephone interviewing employed 

industry standard random-digit dialing and computer assisted telephone interviewing (CATI). 

A total of five surveys were administered via dual-frame telephone interview to a random national 

sample of U.S. adults. Specific fielding dates and sample sizes are:

 Video Game Consoles - February 27-March 2, 2014. 654 interviews were from the landline 

sample and 350 interviews from the cell phone sample.

 Home Audio Devices - December 19-22, 2013. 679 interviews were from the landline sample 

and 352 interviews from the cell phone sample. 

 Desktop and Portable Computers - December 19-22, 2013. 679 interviews were from the 

landline sample and 352 interviews from the cell phone sample. 

 Mobile Devices – Smart phones and Tablets - December 19-23, 2013. 661 interviews were from 

the landline sample and 350 interviews from the cell phone sample. 

 Televisions - November 14-17, 2013. 654 interviews were from the landline sample and 350 

interviews from the cell phone sample. 

As is common practice in survey research, the data were weighted to reflect the known demographics of 

the population under study. In this survey, weights were applied to cases based on gender, age, race 

and geographic region. As a result, these data can be generalized to the entire U.S. adult population. All 

findings presented in this report derived from the surveys were based on weighted data.

Subsequently, we processed the responses received in category-specific models to estimate the installed 

base of CE and CE usage. The category-specific models are discussed in their respective sections, with 

the more involved computer and monitor usage models described in Appendix B.

The complete phone survey scripts fielded follow.

A.1 Personal Computers (Desktops and Portables)

On another subject...

C1 Thinking about the following COMPUTER products you may have in your home, please indicate how many were 

PLUGGED INTO an electrical outlet in YOUR HOME at some point during the PAST MONTH. If you do not have this 

product, please tell me.

(RECORD A NUMBER FOR EACH. RANGE IS 0-10, DON’T KNOW/NOT SURE, DO NOT HAVE THIS PRODUCT)

A. Personal desktop computer

B. Personal portable computer, such as notebooks, laptops or netbook computers
122

IF ANY COMPUTER WAS PLUGGED IN, C1A OR B (1-10), CONTINUE.

ALL OTHERS SKIP TO NEXT SECTION.

IF C1A (1-10), ASK ‘A’ (PRIMARY DESKTOP) SERIES.

IF C1A (2-10), ASK ‘B’ (SECONDARY DESKTOP) SERIES.

IF C1B (1-10), ASK ‘C’ (PRIMARY PORTABLE) SERIES.

IF C1B (2-10), ASK ‘D’ (SECONDARY PORTABLE) SERIES.

C2-C5 PROGRAMMING NOTE:

ASK ‘A’ (PRIMARY DESKTOP) SERIES BEFORE MOVING ON TO ‘B’ (SECONDARY DESKTOP) SERIES, ETC.

[DISPLAY IF C1A (1-10)]

The next set of questions are about DESKTOP COMPUTERS in your household, including those used in home offices [DISPLAY IF 

C1A (2-20)] (starting with the PRIMARY or MOST USED DESKTOP COMPUTER).

[DISPLAY IF C1A (2-10) BEFORE ‘B’ SERIES]

Now, for the next set of questions, please think about the SECONDARY DESKTOP COMPUTER in your household.

[DISPLAY IF C1B (1-10) BEFORE ‘C’ SERIES]

The next set of questions are related to PORTABLE COMPUTERS, such as notebooks, laptops or netbook computers in your 

household [DISPLAY IF C1B (2-20)] (starting with the PRIMARY or MOST USED PORTABLE COMPUTER).

[DISPLAY IF C1B (2-10) BEFORE ‘D’ SERIES]

Now, for the next set of questions, please think about the SECONDARY PORTABLE COMPUTER, such as notebooks, laptops or 

netbook computers in your household.

C2 I’d like to ask you about how long the [INSERT] computer is used by YOU OR OTHERS in your household. Please 

consider all activities such as email, searching the Internet, watching videos, gaming, playing music, etc. Also please 

include time when the computer is doing any of these activities even if no one is at the computer. 

How much time was the [INSERT] computer used YESTERDAY during the following times? Please answer in hours and 

minutes.

(RECORD A NUMBER. RANGE FOR A IS 0-24, DON’T KNOW; RANGE FOR B IS 0-59, DON’T KNOW. SEPARATE PUNCH 

FOR EACH FOR ‘NOT USED’)

01 During the MORNING hours, before 12:00 noon

02 During the AFTERNOON hours, between 12:00 and 5:00 pm

03 During the EVENING hours, between 5:00 pm and when you go to sleep at night

04 In ONE SESSION OR SITTING of use, BEFORE the EVENING

05 In ONE SESSION OR SITTING of use, in the EVENING

06 Over the whole day

A. HOURS

B. MINUTES

a. Primary desktop

b. Secondary desktop

c. Primary portable

d. Secondary portable
123

C3 After you or someone in your household finishes a session or sitting, that is, one instance of use, how often is the 

[INSERT] computer...

(READ ENTIRE LIST BEFORE RECORDING ONE ANSWER)

01 Always

02 Often

03 About half of the time

04 Occasionally

05 Or, never

99 DON’T KNOW

A. Left ON, during the DAYTIME

B. Put into STANDBY or SLEEP, during the DAYTIME

C. TURNED OFF or SHUT DOWN, during the DAYTIME

D. TURNED OFF or SHUT DOWN, OVERNIGHT

a. Primary desktop

b. Secondary desktop

c. Primary portable

d. Secondary portable

C4 Think of a time you were the FIRST person of the day to use the [INSERT] computer. What did you do to begin using it? 

(READ LIST UNTIL STOPPED. RECORD ONE ANSWER)

01 The computer and monitor were already ON showing the previous screen image

02 The computer was already ON, but the monitor was off. You pressed a key or moved the mouse, and 

INSTANTLY the computer was READY

03 You [DISPLAY FOR C-D SERIES ONLY] (opened the computer lid,) pressed a key, moved the mouse or 

pressed a POWER button, and after a FEW SECONDS the computer was ready to use

04 You pressed the POWER BUTTON on the computer, and WAITED more than 15 seconds until it was ready to 

use

99 DON’T KNOW

a. Primary desktop

b. Secondary desktop

c. Primary portable

d. Secondary portable

C5 How many of the following devices, if any, does the [INSERT] computer have connected to it? 

(RECORD A NUMBER. RANGE IS 0-99, DON’T KNOW)

A. LCD flat monitors including LED. DO NOT COUNT displays that are built in to the computer, such as the 

screen on a laptop, netbook or all-in-one desktop

B. CRT or Tube monitors

C. Computer speaker systems without Subwoofer

D. Computer speaker systems with Subwoofer

a. Primary desktop

b. Secondary desktop

c. Primary portable

d. Secondary portable

A.2 Home Audio 

A1 For each of the following AUDIO products, you may have in your home, please indicate how many were PLUGGED 

INTO an electrical outlet in YOUR HOME at some point in the PAST MONTH. If you do not have this product, please 

tell me.
124

(RECORD A NUMBER FOR EACH. RANGE IS 0-10, DO NOT HAVE THIS PRODUCT, DON’T KNOW/NOT SURE)

A. Speaker dock that has a plug-in connection for an MP3 player, smartphone or tablet

B. Shelf stereo system, also called Mini or Compact stereo systems

IF HAVE ANY SPEAKER DOCKS, A1A (1-10), CONTINUE.

ALL OTHERS SKIP TO INSTRUCTIONS BEFORE A4

Now, please answer the next few questions about a speaker dock that has a plug-in connection that you use with your MP3 

player, smartphone or tablet. [DISPLAY IF A1A (2-10)] (Please answer thinking about your PRIMARY speaker dock, meaning the 

one you or your household uses MOST OFTEN.)

A2 About how long did you or others in your household use your PRIMARY speaker dock to listen to any audio 

YESTERDAY? 

Please give your answer in hours and minutes. 

(RECORD A NUMBER FOR EACH. RANGE FOR A IS 0-24, DON’T KNOW, RANGE FOR B IS 0-59, DON’T KNOW)

A. Hours

B. Minutes

A3 After you finished using your speaker dock YESTERDAY, how did you turn it OFF? If you did not use your speaker dock 

yesterday, please answer about the LAST DAY YOU USED IT. 

(READ LIST UNTIL STOPPED. RECORD ONE ANSWER) 

01 The power switch or remote control

02 It turns off automatically if you leave it for more than 20 minutes without any audio playing

03 You did not turn it off, you left it on

04 Or, there is no power switch on the speaker dock

99 DON’T KNOW

IF HAVE ANY SHELF STEREO SYSTEMS, A1B (1-10), CONTINUE.

ALL OTHERS SKIP TO NEXT SECTION

Now, please answer the next few questions about a shelf stereo system, also called a Mini or Compact stereo system. [DISPLAY 

IF A1B (2-10)] (Please answer thinking about your PRIMARY shelf stereo system, meaning the one you or your household uses 

MOST OFTEN.)

A4 About how long did you or others in your household use your PRIMARY shelf stereo system to listen to any audio 

YESTERDAY? 

Please give your answer in hours and minutes. 

(RECORD A NUMBER FOR EACH. RANGE FOR A IS 0-24, DON’T KNOW, RANGE FOR B IS 0-59, DON’T KNOW)

A. Hours

B. Minutes

A5 After you finished using your shelf stereo system YESTERDAY, how did you turn it OFF? If you did not use your shelf 

stereo system yesterday please answer about the LAST DAY YOU USED IT.

(READ LIST UNTIL STOPPED. RECORD ONE ANSWER) 

01 The power switch or remote control
125

02 It turns off automatically if you leave it for more than 15 minutes without any audio playing

03 You did not turn it off, you left it on

04 Or, there is no power switch on the stereo system

99 DON’T KNOW

A.3 Mobile Devices (Smartphones and Tablets)

On another subject...

M1 Thinking about all the devices you may have in your home, how many of each of the following did YOU USE in the 

PAST MONTH? If you do not have this product, please tell me.

(RECORD A NUMBER FOR EACH. RANGE IS 0-20, DON’T KNOW/NOT SURE, DO NOT HAVE THIS PRODUCT)

A. Smartphones, such as an iPhone, Android, Windows Phone, etc.

B. Tablet computers, such as an iPad, Kindle Fire, Galaxy, etc.

IF USED EITHER DEVICE, M1A OR M1B (1-20), CONTINUE WITH INSTRUCTIONS BELOW.

ALL OTHERS SKIP TO NEXT SECTION

ASK ‘B’ (PRIMARY TABLET) SERIES IF M1B (1-20)

ASK M2C (SECONDARY TABLET) IF M1B (2-20)

M2-M6 PROGRAMMING NOTE:

ASK ‘A’ (SMARTPHONE) SERIES BEFORE MOVING ON TO ‘B’ (PRIMARY TABLET) SERIES.

ASK M2C (SECONDARY TABLET) AFTER M2A/B SERIES, BUT NOT FOR M3-M6

[DISPLAY IF M1A (1-20)]

For the next few questions, please think about the smartphone that YOU USE MOST OFTEN.

[DISPLAY IF M1B (1-20) BEFORE ‘B’ SERIES]

Now, for the next set of questions, please think about the primary tablet that YOU USE MOST OFTEN.

[DISPLAY IF M1B (2-20) BEFORE M2C]

For the next question, please think about the secondary tablet that YOU USE SECOND MOST OFTEN.

M2 How much time did you or someone else in your household USE your [INSERT] YESTERDAY? 

(RECORD A NUMBER. RANGE FOR A IS 0-24, DON’T KNOW; RANGE FOR B IS 0-59, DON’T KNOW)

A. HOURS

B.MINUTES

a. Smartphone

b. Primary tablet

c. Secondary tablet

M3 How many TIMES LAST WEEK did you or someone else in your household plug in and CHARGE your [INSERT]? Please 

include any time charging at home or anywhere else. Also, please include any times you have charged more than 

once in a day.

(RECORD A NUMBER. RANGE IS 0-70, DON’T KNOW)
126

a. Smartphone

b. Primary tablet

M4 Thinking about the LAST TIME YOU charged your [INSERT], what was the battery level...

[RECORD ONE ANSWER]

01 Fully charged

02 75% to 99% charged

03 50% to 74% charged

04 25% to 49% charged

05 1% to 24% charged

06 Or, fully drained

99 DON’T KNOW

A. Just BEFORE you charged it

B. Just AFTER you charged it

a. Smartphone

b. Primary tablet

M5 Now, thinking only about YESTERDAY, or the LAST DAY YOU charged your [INSERT] before today, for how much time 

was your [INSERT] plugged in for charging through the following power sources? Please answer in hours and minutes.

(RECORD A NUMBER. RANGE FOR A IS 0-24, DON’T KNOW; RANGE FOR B IS 0-59, DON’T KNOW)

01 Using the original brand name charger that came with your device

02 Using a replacement or aftermarket charger, a car charger, or a USB port charging from a computer, speaker 

system, etc.

A. HOURS

B. MINUTES

a. Smartphone

b. Primary tablet

[ASK IF M5 (01-02)A (1-24) OR M5(01-02)B (1-59)]

M6 Again, thinking only about YESTERDAY, or the LAST DAY YOU charged your [INSERT], how much time was your 

[INSERT]’s CHARGER PLUGGED INTO THE WALL, regardless of whether the device was connected to the charger or 

not? Please answer in hours and minutes.

(RECORD A NUMBER. RANGE FOR A IS 0-24, DON’T KNOW; RANGE FOR B IS 0-59, DON’T KNOW)

A. HOURS

B. MINUTES

a. Smartphone

b. Primary tablet

A.4 Televisions

How many of each of the following devices were PLUGGED INTO an electrical outlet in your home at some point during the 

PAST MONTH? 

(RECORD NUMBER FOR EACH. RANGE IS 0-20, DON’T KNOW/NOT SURE)

[DO NOT RANDOMIZE ITEMS]

01 Televisions

02 Amplifier or home speaker systems, such as external speakers for a TV or a stereo system. Do not include 

portable stereos or speakers used with computers.
127

03 Digital media streaming device which streams video content from the Internet or networked computer, 

such as Apple TV, Roku or Chromecast. Do not count Blu-Ray or DVD players that have this feature.

[ASK IF V1A (1-20)]

V2 Please think about all the different TVs in your household and the ways in which you receive television programming 

such as cable, satellite, fiber to the home, Internet or an antenna that may mount on your roof or an antenna that sits 

on or near the TV. 

In which of the following ways, if any, do you receive television programming on the TVs in your home? 

(READ LIST. RECORD AS MANY AS APPLY. WAIT FOR YES OR NO FOR EACH. IF YES TO MORE THAN ONE OF RESPONSES 

1-3, SAY: ‘Please confirm that you subscribe to more than one service’)

[DO NOT RANDOMIZE ITEMS]

01 Cable TV service

02 Satellite TV service

03 Fiber to the home TV service, such as Verizon Fios or AT&T U-verse

04 Antenna TV service

05 Internet TV service

98 I DON’T RECEIVE PROGRAMMING ON ANY OF MY TVS

99 DON’T KNOW

IF TELEVISION WAS PLUGGED IN DURING PAST MONTH, V1A (1-20), CONTINUE.

ALL OTHERS SKIP TO INSTRUCTIONS BEFORE V13

IF ONLY ONE TELEVISION, V1A (1), ONLY ASK FOR PRIMARY.

IF TWO TELEVISIONS, V1A (2), ASK FOR PRIMARY AND SECONDARY.

IF THREE TELEVISIONS, V1A (3-10), ASK FOR PRIMARY, SECONDARY, THIRD,

IF FOUR OR MORE TELEVISIONS, V1A (4-20), ASK FOR PRIMARY, SECONDARY, THIRD, AND FOURTH 

The next questions are about TELEVISIONS in your household, starting with the PRIMARY, or most-watched TV.

[SHOW IF V1A (2-20)]

For the next few questions, please answer for up to four TVs owned by your household. Please consider the one used the 

MOST the PRIMARY TV, the one used the SECOND most the SECOND TV, the one used the THIRD most as the THIRD TV and the 

one used the FOURTH most as the FOURTH TV.

ASK V3-V8 ‘A’ SERIES BEFORE GOING TO THE ‘B’ SERIES, ETC.

V3 Is the [INSERT] television that you own a . . . 

(READ ENTIRE LIST BEFORE RECORDING ONE ANSWER.]

[DO NOT RANDOMIZE LIST OR ITEMS]

01 LCD or LED Flat-panel TV

02 Plasma Flat-panel TV

03 Tube TV, also known as a direct-view CRT

04 Front or Rear Projection TV
128

99 DON’T KNOW/NOT SURE

A. Primary

B. Second

C. Third

D. Fourth

V4 What is the approximate screen size IN INCHES of the [INSERT] TV that you own? If you are not sure, please use your 

best estimate. 

(RECORD NUMBER. RANGE IS 5-72, DON’T KNOW/NOT SURE)

(PROBE FOR BEST GUESS BEFORE ACCEPTING DON’T KNOW)

A. Primary

B. Second

C. Third

D. Fourth

V5 What is the age IN YEARS of the [INSERT] TV that you own? If you are not sure, please use your best estimate.

(RECORD NUMBER. RANGE 1-50, DON’T KNOW/NOT SURE)

(IF RESPONDENT SAYS THE TV IS NEW, AS IN LESS THAN ONE YEAR, RECORD AS 1. PROBE FOR BEST GUESS BEFORE 

ACCEPTING DON’T KNOW)

A. Primary

B. Second

C. Third

D. Fourth

PROGRAMMING NOTE: THIS WORDING SHOULD ONLY BE DISPLAYED DURING THE ‘A’ SERIES (PRIMARY TELEVISION)

Next, I am going to ask you a couple of questions about how you and those in your household use the TVs you currently have 

plugged into an electrical outlet. I am going to use two terms that I will define for you.

The first term is ‘turned on’. ‘Turned on’ means that the television’s power is in the ON mode regardless of whether someone

is actually using it. For example, a TV is turned on when there is a picture on the screen or sound being emitted, as well as 

when it has a screen saver on while waiting for users.

The second term is ‘active use’. ‘Active use’ means that the television is on AND being used by someone. For example, when a 

TV is in active use, someone is using it to watch TV, a movie, play games or is actively listening to the TV.

V6A Now, thinking of the [INSERT] TV that you own, during the PAST 24 HOURS, how much time was it turned on? If you 

are not sure, please give your best estimate. 

(RECORD NUMBER. RANGE FOR HOURS (a) IS 0-24, DON’T KNOW AND RANGE FOR MINUTES (b) IS 0-59, DON’T 

KNOW) 

A. Primary

B. Second

C. Third

D. Fourth

a. Hours

b. Minutes

[ASK FOR EACH V6A A-D ([a (HOURS) IS 1-24] OR [b (MINUTES) IS 1-59)]]
129

[IF V6A A-D a (0), AUTOPUNCH V6B A-D a AS 0]

V6B And during the PAST 24 HOURS, how much time was the [INSERT] TV in active use? If you are not sure, please give 

your best estimate.

(RECORD NUMBER. RANGE FOR HOURS (a) IS 0-ANSWER GIVEN IN V6A, DON’T KNOW AND RANGE FOR MINUTES (b) 

IS 0-59, DON’T KNOW) 

A. Primary

B. Second

C. Third

D. Fourth

a. Hours

b. Minutes

V7 Which of the following devices, if any, are connected to your [INSERT] television?

(READ LIST. RECORD AS MANY AS APPLY. WAIT FOR YES OR NO FOR EACH)

[DO NOT RANDOMIZE LIST]

01 Receiver or set-top-box with DVR functionality

02 Receiver or set-top-box WITHOUT DVR functionality

03 Digital media streaming device with DVR functionality

04 Digital media streaming device WITHOUT DVR functionality

98 NONE OF THESE

99 DON’T KNOW

A. Primary

B. Second

C. Third 

D. Fourth

[ASK FOR EACH MENTION, V7A-D (01-02)]

V8 Which of the following features, if any, does your receiver or set-top box connected to your [INSERT] television have?

(READ LIST. RECORD AS MANY AS APPLY. WAIT FOR YES OR NOT FOR EACH)

01 Ability to record shows in one room and play them back in another room 

02 Ability to pause and rewind LIVE TV in one room and resume viewing in another room

03 Ability to record FIVE or more shows at once

98 NONE OF THESE

99 DON’T KNOW

A. Primary

B. Second

C. Third 

D. Fourth

V9A and V10 OMITTED

IF A DIGITAL MEDIA PLAYER WAS PLUGGED IN DURING PAST MONTH, V1C (1-20), CONTINUE.

ALL OTHERS SKIP TO INSTRUCTION BEFORE V13
130

The next questions are about streaming video from your digital media streaming device which streams video content from the

Internet or networked computer, such as Apple TV, Roku or Chromecast. For this section, DO NOT count Blu-Ray or DVD players 

that have this feature.

V11 Please think of the most recent occasion when you were the FIRST person in your household to use the digital media 

streaming device, to watch streaming video. Did you need to turn ON the digital media streaming device, for 

example, by using a remote control or power switch? 

01 YES

02 NO

99 DON’T KNOW

V12 How long did you or anyone in your household watch streaming video content YESTERDAY using a DIGITAL MEDIA 

STREAMING DEVICE such as Apple TV or Roku? Please do not include video content streamed on other devices such 

as the computer including tablets and laptops, Smart TV or DVD/Blu-Ray player. 

(RECORD NUMBER. RANGE IS 0-24 HOURS AND 0-59 MINUTES, DON’T KNOW)

IF HOME SPEAKER SYSTEM WAS PLUGGED IN DURING PAST MONTH, V1B (1-20), CONTINUE.

ALL OTHERS SKIP TO NEXT SECTION

IF ONLY ONE HOME SPEAKER SYSTEM, V1B (1), ONLY ASK FOR PRIMARY.

IF TWO HOME SPEAKER SYSTEMS, V1B (2), ASK FOR PRIMARY AND SECONDARY.

IF THREE HOME SPEAKER SYSTEMS, V1B (3), ASK FOR PRIMARY, SECONDARY AND THIRD.

IF 4 OR MORE HOME SPEAKER SYSTEMS, V1B (4-20), ASK FOR PRIMARY, SECONDARY, THIRD, AND FOURTH

The next questions are about HOME SPEAKER SYSTEMS, starting with the PRIMARY or most used HOME SPEAKER SYSTEMS. 

Home speaker systems include speakers that are used with TVs, such as ‘Home Theater Systems’, ‘sound-bars,’ amplifiers or 

stereo systems. They do NOT include portable stereos or speakers used with computers.

ASK V13 AND V14 IN SEQUENCE FOR EACH SPEAKER SYSTEM

V13 Please think of the most recent occasion you used the [INSERT] HOME SPEAKER SYSTEM for the FIRST TIME THAT 

DAY. Did you need to turn ON the speaker system, for example, by using a remote control or power switch?

01 YES

02 NO

99 DON’T KNOW

A. Primary

B. Secondary

C. Third

D. Fourth

V14 How long was the [INSERT] speaker system used YESTERDAY, by you or anyone else in your household?

(RECORD NUMBER. RANGE IS 0-24 HOURS (a) AND 0-59 MINUTES (b), NOT USED DON’T KNOW)

A. Primary

B. Secondary

C. Third

D. Fourth

a. Hours

b. Minutes
131

A.5 Video Game Consoles

E1 For each of the following VIDEO GAME CONSOLES, please indicate how many you or someone in your household 

owns.

(RECORD NUMBER FOR EACH. RANGE IS 0-10, DON’T KNOW)

[RANDOMIZE ITEMS]

A. Microsoft Xbox

B. Microsoft Xbox 360

C. Microsoft Xbox One

D. Sony PlayStation 2

E. Sony PlayStation 3

F. Sony PlayStation 4

G. Nintendo GameCube

H. Nintendo Wii

I. Nintendo Wii U

IF OWN ANY VIDEO GAME CONSOLE, E1A-I (1-10), CONTINUE.

ALL OTHERS SKIP TO NEXT SECTION

E2-E7 PROGRAMMING NOTES:

ASK FOR UP TO 4 CONSOLES, E1A-I (1-10), WITH PRIORITY ON:

1. E1B (MICROSOFT XBOX 360)

 2. E1H (NINTENDO Wii)

3. E1E (SONY PLAYSTATION 3)

4. E1D (SONY PLAYSTATION 2)

IF NECESSARY, ASK FOR REMAINING ITEMS (A, C, F, G, I) ACCORDING TO LEAST FILL PRIORITY

NOTE: MORE THAN ONE OF THE SAME CONSOLE CAN BE ASKED ABOUT IN THIS SEQUENCING, AND SHOULD ALWAYS TAKE 

GREATER PRIORITY BEFORE A NON-PRIORITY SYSTEM IS CONSIDERED 

ASK E2-E7 FOR ONE ITEM BEFORE MOVING ONTO E2-E7 FOR THE NEXT ITEM

E2 Please indicate in what year your [INSERT ITEM] was purchased or received as a gift, if you got it BRAND NEW.

(RECORD YEAR FOR EACH. RANGE IS 2000-2014, WAS NOT BRAND NEW, DON’T KNOW)

[RANDOMIZE ITEMS]

A. Microsoft Xbox

B. Microsoft Xbox 360

C. Microsoft Xbox One

D. Sony PlayStation 2

E. Sony PlayStation 3

F. Sony PlayStation 4

G. Nintendo GameCube

H. Nintendo Wii

I. Nintendo Wii U

i. First console
132

ii. Second console

iii. Third console

iv. Fourth console

[ONLY DISPLAY BEFORE FIRST SERIES]

The next few questions will be about the USAGE of your video game console.

Next, we will ask you about HOW you and those in your household use your gaming console(s), in one of the following states:

 TURNED ON—the gaming console’s power is in the ON mode REGARDLESS of whether someone is actually 

using it. This includes time when the console is paused.

 ACTIVE USE—the gaming console is ON AND BEING USED by someone. For example, when a gaming 

console is in active use, someone is using it to play games, watch a movie, etc.

 TURNED OFF—the gaming console is OFF. You turned OFF your gaming console manually or by using a 

voice command.

E3 How much time did your [INSERT ITEM] spend YESTERDAY in each of the following states? Please give your answer in 

hours and minutes. If you did not use your [INSERT ITEM] yesterday, please say so.

(RECORD A NUMBER. RANGE FOR A IS 0-24, DON’T KNOW; RANGE FOR B IS 0-59, DON’T KNOW)

[RANDOMIZE ITEMS]

07 Turned on

08 Actively used

C. HOURS

D. MINUTES

a. Microsoft Xbox

b. Microsoft Xbox 360

c. Microsoft Xbox One

d. Sony PlayStation 2

e. Sony PlayStation 3

f. Sony PlayStation 4

g. Nintendo GameCube

h. Nintendo Wii

i. Nintendo Wii U

i. First console

ii. Second console

iii. Third console

iv. Fourth console

[ASK IF E3 A OR B IS 1 OR MORE FOR ‘ACTIVELY USED’- 02]

E4 During the [INSERT E3A] [DISPLAY IF E3A (1-24)] (hours and) [INSERT E3B] [DISPLAY IF E3B (1-59)] (minutes) your 

[INSERT ITEM] was actively used YESTERDAY, approximately how much of this time was used to do each of the 

following? If you are not sure, please use your best estimate. Please give your answer in hours and minutes.

(RECORD A NUMBER. RANGE FOR A IS 0-ANSWER FROM E3A (02), DON’T KNOW; RANGE FOR B IS 0-59, DON’T 

KNOW)

[RANDOMIZE ITEMS]

01 Play games

02 Stream media from the video game console or Internet

03 DVD and/or Blu-Ray playback
133

A. HOURS

B. MINUTES

a. Microsoft Xbox

b. Microsoft Xbox 360

c. Microsoft Xbox One

d. Sony PlayStation 2

e. Sony PlayStation 3

f. Sony PlayStation 4

g. Nintendo GameCube

h. Nintendo Wii

i. Nintendo Wii U

i. First console

ii. Second console

iii. Third console

iv. Fourth console

E5 Thinking about the last time when you were the FIRST PERSON to ‘actively use’ the [INSERT ITEM] on a day, which 

statement best describes your gaming console?

(READ ENTIRE LIST BEFORE RECORDING ONE ANSWER)

01 It was already turned ON and ready to use

02 It was turned OFF and you needed to turn it on to use it

99 DON’T KNOW

A. Microsoft Xbox

B. Microsoft Xbox 360

C. Microsoft Xbox One

D. Sony PlayStation 2

E. Sony PlayStation 3

F. Sony PlayStation 4

G. Nintendo GameCube

H. Nintendo Wii

I. Nintendo Wii U

i. First console

ii. Second console

iii. Third console

iv. Fourth console

E6 Does your [INSERT ITEM] automatically turn off after a sustained period of inactivity? 

[RANDOMIZE ITEMS]

01 YES

02 NO

99 DON’T KNOW

A. Microsoft Xbox

B. Microsoft Xbox 360

C. Microsoft Xbox One

D. Sony PlayStation 2

E. Sony PlayStation 3

F. Sony PlayStation 4

G. Nintendo GameCube

H. Nintendo Wii
134

I. Nintendo Wii U

i. First console

ii. Second console

iii. Third console

iv. Fourth console

[ASK FOR EACH MENTION E6A-I (01)]

E7 After approximately how many hours does the [INSERT ITEM] automatically turn off?

(RECORD A NUMBER. RANGE IS 1-24, DON’T KNOW)

[RANDOMIZE ITEMS]

A. Microsoft Xbox

B. Microsoft Xbox 360

C. Microsoft Xbox One

D. Sony PlayStation 2

E. Sony PlayStation 3

F. Sony PlayStation 4

G. Nintendo GameCube

H. Nintendo Wii

I. Nintendo Wii U

i. First console

ii. Second console

iii. Third console

iv. Fourth console
135

Appendix B – Energy and Usage Models

We discuss in detail several models used to calculate the usage time and energy consumption for 

desktop and portable computer, smart phones, tablets, and video game consoles.

B.1 Energy Models — Personal Computers (Desktops and Portables)

In this appendix, we describe the energy model used to calculate the unit and annual energy 

consumption for desktop and portable personal computers (PCs).

We reference specific questions in the survey to obtain values certain variables in the energy model. 

These are indicated in bold green, e.g., <C5.A> references survey question 5, sub-question A in the 

computer survey. See Appendix A.1 for the survey questions.

Table B-1: Variables directly measured in the CE Usage Survey.

Survey Question Purpose Measure Variable

C1.# Number of plugged-in ... Installed base Count

C2.A Desktop PCs 

C2.B Portable PCs 

C2.## Usage time ... Usage time Time (hh:mm)

C2.01 During the morning hours (before 12 noon) 

 

C2.02 During the afternoon hours (between 12 and 5pm) 

 

C2.03 During the evening hours (between 5pm and when 

you go to sleep at night)

 

 

C2.04 In one session of use, before the evening 

 

 

C2.05 In one session of use, in the evening 

 

 

C2.06 Over the whole day 

 

 

C3.# Frequency that the PC is ... Manual power 

management (PM) 

routines

Probability

C2.A Left on, during the daytime 

C2.B Put into sleep, during the daytime 

C2.C Turned off, during the day time 

C2.D Turned off, at night 

 

C4 Initial state of the PC for the day Auto PM settings Choice 

C5.# Number of devices connected to PC ... Indirect accounting 

of AIO desktop PCs

Count

C2.A LCD monitors 

C2.B CRT monitors 

C2.C Speakers without subwoofer -

C2.D Speakers with subwoofer -

B.1.1 Plugged-In Install Base

The installed base is calculated from the total sum of desktop or portable PCs reported by each 

respondent ( and ), and weighted to the U.S. household distribution.

 

 

 

∑ 

 

 

 

 

 

∑ 

 

 
136

where

 is the sum of weights of each survey response to all U.S. households

 is the number of U.S. households

 is the set of survey responses

 is weight of the th survey response

 is number of desktop PCs reported by the th survey response <C5.A>

 is number of desktop PCs reported by the th survey response <C1.B>

We also distinguish All-in-One (AIO) desktop PCs from tower desktop PCs by noting, for each primary or 

secondary PC, if the PC has no monitor (LCD or CRT) connected to it, i.e., <C5.A=0 and 

C5.B=0>.

B.1.2 Operational Modes

PCs can enter different operational modes with different power draws after various time durations. We 

previously defined the modes used in our energy model (see Section 3.4). We declare these as variables 

in this model (see Table B-2). 

Table B-2: Variables for power draw and time threshold of various operational modes.

Operational Mode Active Short Idle Long Idle Sleep Off

Power Draw 

Time Threshold 

We define the threshold time durations after which the lower power modes are triggered in Table B-3. 

These thresholds are calculated based on the ENERGY STAR specification and as measured in the 

ENERGY STAR Qualified Product List (QPL) (EPA 2013).

Table B-3: Time Thresholds at the start of a post-session after which the PC enters various operational modes.

Time Threshold

ENERGY STAR

Spec. 

(minutes)

Default in QPL (minutes) Representative

Desktops Portables Desktops Portables§

Average Median Average Median

 † 0 0

 5 - - - - 5 5

 15 25 15 23 10 15 10

 30 13 30 112 25 30 25

 60*

- - - - 60 60

 ‡ 

§ We choose shorter time thresholds for portable PCs which are consistent with their behavior to conserve energy when 

occasionally running on battery.

† Zero-valued variable introduced for consistency in some equations.

‡ Infinity-valued variable introduced for consistency in some equations.

* Assumed, specified for our analysis.

B.1.2.1 Operational Modes for External Power Supplies of Portable PCs

Portable PCs have additional operational modes due to their external power supplies (EPS) which charge 

the portable PC batteries, from which the PCs may be unplugged, and which may be unplugged from the 

wall socket altogether. This leads to increased energy consumption for charging, and decreased energy 
137

consumption when the portable PC is unplugged. In our model, we calculate the time spent in these 

modes as a fraction of the usage time of the portable PC in various base operational modes (see Table 

B-4; see Section B.1.7.2 for more details). These modes are originally defined by DOE (2012).

Table B-4: Variables for power draw and portion of time of various operational modes for portable PCs due to their external 

power source (EPS).

Base Portable PC Mode

Active, Short Idle, and 

Long Idle

Off

EPS Mode Charging (Active) Charging 

(Off)

Off Unplugged EPS Unplugged

Portable PC + EPS Power Draw 

% time of PC mode in EPS mode 

where

 W, i.e., no power draw

 ( ) 

 

B.1.3 Usage Modeling

We expect usage to vary at different times of the day. Therefore, we identify several day periods and 

model the usage and energy consumption for each period. Then, we sum them to get the total usage 

and energy consumption for the whole day, and, ultimately, the UEC for the whole year and AEC for the 

installed base.

B.1.3.1 Day Periods

Based on our analysis of the amount of computer usage across a day (ATUS 2012), we model computer 

usage by period during the day: Pre-Evening (morning and afternoon), Evening, and Night. Restricting to 

Home/Yard (TEWHERE = 1), we considered activities with potentially major components of computer 

usage [TRCODE]:

 Financial management [20901], n=355

 Work, main job [50101], n=9720

 Work, other job(s) [50102] , n=370

 Playing Games [120307], n=1381

 Computer use for leisure (exc. Games) [120308], n=1902

 Computer use (Volunteering) [150101] , n=157
138

Figure B-1: Probability density of performing activities related to using computers (ATUS 2012).

From Figure B-1, we can estimate default boundaries and durations for the three day periods. However, 

some survey responses indicated that the active use duration within certain periods exceed the defined 

bounds. Therefore, we allow for the day periods to be adjustable by formulas presented in Table B-5.

Table B-5: Time durations for different day periods.

Day Period 

 

Formula

Default Example Survey Response

Range Duration 

[hours]

Reported 

 

Adjusted 

 

 ( ) 7am-5pm 10 11 11

 ( ) 5pm-11pm 6 7 7

 11pm-7am 8 - 6

The time periods sum to 24 hours in a whole day, i.e., 

 

Next, we describe how we compute energy consumption for the pre-evening, evening, and night 

periods. The calculations for the pre-evening and evening periods are similar and will henceforth be 

called daytime periods.

B.1.3.1.1 Sample Energy Consumption across Daytime Periods

For daytime periods, we model the number of active use sessions, which include “micro-breaks” within 

each session, and post-sessions between them. After each session, the PC may gradually go into a lower 

power operational mode. The minimum power mode depends on the automatic power management 

(PM) settings, and whether household occupants manually put the PC into sleep or turn it off. We model 

the night period as having no active use sessions, so its energy consumption is only due to automatic PM 

settings and manual power management. Figure B-2 shows two examples of the energy consumption as 

calculated by the energy usage model.

0%

2%

4%

6%

8%

10%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

% U.S. Population

Computer Usage Start Time (Hour)
139

 

Based on power draw by mode, survey responses of usage duration for each session and how many sessions per 

day period. Left: PC left on during the day time, PM auto-hibernate. Right: PC left on during the daytime, PM long 

idle enabled, manually put to sleep at night.

Figure B-2: Examples of energy consumption modeling for a day.

B.1.3.2 Daytime Periods

We model usage in the day time (pre-evening and evening) as consisting of active use sessions separated 

by post-session periods. The number of sessions is:

 

 

 

where

 is the total usage duration in the daytime period <C2.01, C2.02, C2.03>

 is the typical session duration <C2.04, C2.05>

B.1.3.3 Usage Session

We assume that users take a “micro-break” after one hour during each active use session (OSHA 1997, 

UC Berkeley 2014). We assume that each break lasts about 10 minutes (average of short and long idle 

thresholds). This gives 5 minutes for short-idle mode to activate and 5 minutes to be in that mode. The 

usage time for each operational mode in each session computed as:

Daytime: Usage Session

 

 

   

 

 

 

 

 

 

 

 

 

 

 

where

 ( ) ⌊

 

 ⌋ is the number of breaks per session

One 50min-long

session

Two 2hr-long

sessions

Active

Short Idle

Long Idle

Sleep

Off

Power Draw

by Mode

No

sessions

Pre-Evening

~7am – 5pm

Evening

~5pm – 11pm

Night

~11pm – 7am

One 30min-long

session

One 2hr-long

sessions

No

Sessions

Pre-Evening

~7am – 5pm

Evening

~5pm – 11pm

Night

~11pm – 7am

Usage session

Post-session
140

 is the active usage time threshold until a short break

B.1.3.4 Post-Session

A post-Session is defined as the following unused period until the next active usage session. This 

calculation only applies if there is at least one active use session in the daytime period, i.e., 

 . See Section B.1.3.5 for how we calculate for cases with no active session. Each post-session is defined 

with:

 ⌈ ⌉

 

 

 

where

 is the duration of the daytime period ( or )

After a usage session, i.e., post-session, the PC may enter into lower power modes after a series of time 

thresholds. These depend on the total time of the post-session before the next usage session, and the 

power management routines (manual user behavior) and automated settings.

B.1.3.4.1 Manual Power Management Routines

We asked U.S. adults how often they manually turned their PC off or put it to sleep <C3> to get 

measures for the following variables:

 is the probability of manually switching OFF after each daytime use <C3.C, C3.D>

 is the probability of manually putting computer into SLEEP during daytime <C3.B>

 is the probability of leaving computer ON after use during daytime <C3.A>

 

We map numeric probability values from discrete option values in the survey responses with:

 

{

 

 

 

 

 

 

 

 

 

 ̅ 

 

where

 ̅ is the average of the probability metric

 { }
141

B.1.3.4.2 Automated Power Management Settings Modes

The automated power management settings, , measured in <C4> is defined as:

 

{

 

 

 

 

 

 

 

 

 

 

Note that is enabled by using auto-hibernate under advanced power management settings40. 

Also, it is not defined in ENERGYSTAR, so there would not be a default time for it to activate. 

B.1.3.4.3 Usage Time by Operational Mode in Post-Session

The usage time for each operational mode in each post-session is:

Daytime: Post-Session

 

 

 

 

 

 

 

  

 

 ( )

 

 

 ( )

 

 

 ( )

 

 

 ( ) 

 

 ( ) 

where

 , , , , and are the time durations the PC is in active, short idle, long 

idle, sleep, and off modes, respectively, in a post-session. These are functions of and 

 :

 ( ) ( )( ( ) ) ( )( )

 ( ) ( )( ( ) ) ( )( )

 ( ) ( )( ( ) ) ( )( )

 ( ) ( )( ( ) ) ( )( )

 ( ) ( )( ( ) ) ( )( )

B.1.3.5 Non-Session

If there is no active use session during a daytime period, then power draw depends only on the power 

management settings. We define one “non-Session” for that period with the following characteristics:

 [ ] {

 

 

 

40 For example, in Windows XP: http://www.microsoft.com/resources/documentation/windows/xp/all/proddocs/enus/pwrmn_automatic_hibernation.mspx?mfr=true
142

Daytime: Non-Session

 

     

 

 

 

 ( )

 

 ( )

 

 ( ) 

 

 ( ) 

where

 is the total duration for the daytime period, { }

B.1.3.6 Total Usage by Operational Mode in Daytime Period

Combining the usage time for all sessions and post-sessions, we get the total usage by operational

mode for the daytime period:

Daytime

 

 

 

 

 

 

 

  

 

 

 

 

 

 

 { }

B.1.4 Pre-Evening Period

To determine the usage time in the evening period, we use the calculations for daytime periods with the 

following substitutions:

 

 

 <C2.03>

 

   <C2.01, C2.02>

 

B.1.5 Evening Period

To determine the usage time in the evening period, we use the calculations for daytime periods with the 

following substitutions:

 

 

 <C2.03>

 

 <C2.05>

 

B.1.6 Night Period

We assume that the computer is not actively used at night, so this period does not have any sessions 

and power draw depends only on the power management settings. Since we asked U.S. adults only 
143

whether or not they turned off the PC at night, we estimate the probability of leaving the PC on or 

putting it to sleep at night based on the ratio between leaving on and sleep for the day:

 

 

 

 

( 

 

)

 

   

Therefore, we calculate the time in operational modes at night as:

Night

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  

 ( )

 

 

  

 ( )

 

 

  

 ( ) 

 

 

 

 

  

 ( ) 

 

 

where

 

 

is the probability of leaving the PC on at night

 

 

is the probability of putting the PC to sleep at night

 

 

is the probability of manually turning the PC off at night <C3.D>

 ( ) {

 

 ( ) 

 

 

 

 ( ) is the empirical probability distribution of power management modes

B.1.7 Whole Day

The usage time and energy consumption for desktop and portable PCs differ slightly due to the external 

power modes of portable PCs.

B.1.7.1 Desktop PC

The usage time for the whole day is the sum of the energy consumption for the pre-evening, evening, 

and night sessions for desktop PCs are:

Whole Day — Desktop PCs: Usage Time

 

B.1.7.2 Portable PCs

For portable PCs, we model additional operational modes due to the external power supply (EPS) and 

apply the following adjustments to calculate the usage time for several modes:
144

 ( ) the total time 

spent charging during active-idle and off modes.

 where we scale the time in off mode by down to accommodate for the 

times in additional modes: charging (off), unplugged, EPS unplugged

 

 

The usage times for the following modes are unchanged: , , , and . 

We define the total time plugged in for the whole day as: 

Whole Day — Portable PCs: Usage Time

 

 

 

This excludes the time when the EPS is unplugged from the wall socket, , i.e.,

 

Also, note that the usage time for charging overlaps with active and off modes, i.e.,

 

B.1.8 References

ATUS. 2012. “American Time Use Survey — 2012 Microdata Files.” Jun. 20, 2013. United States 

Department of Labor. http://www.bls.gov/tus/datafiles_2012.htm. Retrieved Oct. 30, 2013.

UC Berkeley. 2014. “Safe Computer Use Tips.” University of California Ergonomics. 

http://ergo.berkeley.edu/services/computer_use.php. Retrieved Mar. 7, 2014.

DOE. 2012. “Rulemaking for Battery Chargers and External Power Supplies Energy Conservation 

Standard. Energy Use Analysis Spreadsheet.” Feb. 17, 2012.

http://www.regulations.gov/#!documentDetail;D=EERE-2008-BT-STD-0005-0084. Retrieved Feb. 6, 

2014.

EPA. 2013. “ENERGY STAR Computer Specification Version 5.2 — Qualified Product List.” Sept. 6, 2013. 

http://www.energystar.gov/products/specs/computer_specification_version_6_0_pd. Retrieved 

Sept. 16, 2013.

OSHA (Occupational Safety and Health Administration). 1997. “Working Safely with Video Display 

Terminals.” U.S. Department of Labor. https://www.osha.gov/Publications/osha3092.pdf. Retrieved 

Sept. 16, 2013.

UC Berkeley. 2014. “Safe Computer Use Tips.” University of California Ergonomics. 

http://ergo.berkeley.edu/services/computer_use.php. Retrieved Mar. 7, 2014.
145

B.2 Energy Usage Models — Mobile Devices (Tablets and Smartphones)

In this appendix, we describe the energy model used to calculate the unit and annual energy 

consumption for mobile devices: tablets and smartphones.

We reference specific questions in the survey to obtain numeric values certain variables in the energy 

model. These are indicated in bold green, e.g., <M1.A> references survey question 1, sub-question A in 

the mobile survey. See Appendix A – CE Usage Surveys for the survey questions.

Table B-6: Variables directly measured in the CE Usage Survey.

Survey Question Purpose Measure Variable

M1.# Number of plugged-in ... Installed base Count

M2.A Smartphones 

M2.B Tablets 

M2 Usage time over the whole day Usage time Time (hh:mm) 

M3 Number of charge sessions / week Charge cycles Count 

M4.# Battery life level ... Charge cycles 0-100

M4.A Before charging 

M4.B After charging 

M5.## Time device is plugged into ... Charger preference Time (hh:mm)

M5.01 Original charger 

M5.02 Other chargers 

M6 Plugged-in time of charger Unplugged mode Time (hh:mm) 

B.2.1 Plugged-In Install Base

The installed base is calculated from the total sum of desktop or portable PCs reported by each 

respondent ( and ), and weighted to the U.S. household distribution.

 

 

 

∑ 

 

 

 

 

 

∑ 

 

 

where

 is the sum of weights of each survey response to all U.S. households

 is the number of U.S. households

 is the set of survey responses

 is weight of the th survey response

 is number of smartphones reported by the th survey response <M1.A>

 is number of tablets reported by the th survey response <M1.B>

B.2.2 Energy Consumption

We model the energy consumption by how much energy is consumed to charge the battery, how much 

is consumed while idle, and how much is consumed because the battery charger is left plugged into the 

wall socket after charging. Specifically, we consider the following modes:
146

 Charging: when replenishing the battery of the mobile device to its fully capacity with an 

additional energy loss due to the inefficiency in the charger.

 Idle: when the mobile device has its screen off, is connected to its charger, but not charging. The 

power draw in this mode is higher than the standby power draw when the mobile device is 

running on its battery unplugged from the charger.

 Unplugged: when the mobile device is unplugged from its charger, but the charger is still 

plugged into the wall socket. The power draw is solely due to the charger. 

 BC Unplugged: when the charger is unplugged from the wall socket. The power draw is 0W.

B.2.2.1 Charging

The energy consumed for charging the mobile devices depends on how many times it is charged, and 

how much it is charged each time from before charging (pre-charge) to after charging (post-charge), 

represented by the battery level (state of charge). The energy consumption for charging per day, 

 , is calculated as:

Charging: Energy Consumption

 

 

 

 

( )

 (

 

 

 

 

 )

where 

 is the number of full charge cycles per day as the average sum of partial charge 

cycles

 the number of times the mobile device is charged per week <M3>

 the average battery level before a typical instance of charging <M4.A>

 the average battery level after a typical instance of charging <M4.B>

and where is the energy used for each charging session, which depends on how much energy is 

needed to fully charge the battery, which charger is used (original or others), and the efficiency of the 

chargers, with

 the representative battery capacity in Wh

 the representative original wall charger efficiency while charging

 the representative charger efficiency of other chargers (e.g., aftermarket charger, 

counterfeit charger, USB port of a computer or speaker system, in car 12V)

 

 

 

the portion of time (%) spent charging with the representative 

original wall charger 

 the portion of time of charging with the representative other wall 

charger
147

 the time plugged into the original wall charger <M5.A>

 the time plugged into other chargers <M5.B>

B.2.2.2 Usage

Although not directly used in our energy model, we asked U.S. adults about how much they used their 

mobile devices yesterday <M2>. To validate our charging energy model, we found a moderate 

correlation between usage, and number of charge sessions (r=0.25) and number of full charge cycles 

(r=0.23).

B.2.2.3 Idle

The energy consumption when the mobile device is idle (plugged into the charger with screen off) is

Idle: Energy Consumption

 

 

 

 

 

 

where 

 is the number of full charge cycles per day

 is the power draw in idle mode weighted for the portion of time using the original and 

other charges with 

 and 

 power draws, respectively

 is the time spent per day idle mode

 is the time spent per day charging the battery

 is the time to fully recharge the battery from 0-100%

B.2.2.4 Unplugged

The power draw of battery chargers with the device unplugged may account for a relatively significant 

portion of the mobile device energy consumption. We therefore account for this by evaluating the time 

that the chargers are left plugged into the wall after charging.

The energy consumption of the mobile device when unplugged from the charger is

Unplugged: Energy Consumption

 

 

 {

 

 

where 
148

 is the power draw of the representative original charger with the mobile device 

unplugged

 is the power draw of the representative alternative charger (others) 

 is the amount of time yesterday the original charger was plugged into the 

wall while not charging

 is the amount of time yesterday the original charger was plugged into the 

wall (with and without charging) <M6>

 is the plugged-in time for other chargers after charging, where we assume that

other chargers are plugged in for the same amount of time as the original charger if they are 

used

B.2.2.5 Representative Weights for Mobile Device and Charger Models

We estimate the representative weights, , from an analysis of the usage share of popular mobile device models (see 

Table B-10 for smartphones and Table B-7 for tablets). Usage share is similar to installed base, but refers 

to the distribution of device models by their usage popularity instead of survey reported ownership. We 

refer to data sources which measured app usage or website visits of unique users to get an estimate for 

the usage share of mobile device models.

The representative battery and chargers depend on the estimated usage share, , of various popular 

mobile devices and their respective chargers:

 ∑ 

 

 ∑ 

 

∑ 

 

 

where 

 is the set of models of the mobile device category, e.g., { }

 is the battery capacity of the th mobile device model

 is the efficiency of the original charger of the th mobile device model

We represent the efficiency of other chargers by an average of several documented aftermarket 

chargers:

 ∑ 

 

where 

 is the efficiency of the th alternative charger

We calculate the representative power draws as:
149

 ∑ 

 

 ∑ 

 

where 

 is the power draw of the th original charger with the mobile device unplugged

 is the power draw of the th alternative charger with the mobile device unplugged; we 

assume equal weighting, for lack of data regarding the usage share of alternative chargers.

Table B-7: Usage share of popular tablet models used to derive weights, , to estimate the representative battery capacity 

and power draw values for tablets.

Usage Base Share

Dec 13 Dec 13 Dec 13 Sep 13 Sep 

13 Jun 13 Dec 13

Aggregate

Representative 

Weights

 

Model OS Mix-Panel 

2014b

Fiksu 

2014

StatCounter 

2013b

Chitika 

2013

Localytics 

2013

Magid

2013

CEA 

2014*

iPad mini 2 iOS 0.8% 1.1%

79%

- - - 0.7% -

iPad Air iOS 3.0% 4.3% - - - 2.7% -

iPad mini 1 iOS 16% 21%

81%

- - 21%†14% 16%

iPad 4 iOS 14% 20% - - 20%†13% 15%

iPad 3 iOS 15% 16% - - 18%†12% 14%

iPad 2 iOS 32% 37% - - 40%†26% 30%

iPad 1 iOS 3.4% 0.3% - - 1.4% -

Kindle Fire HD Android - - 8.0% 6.7% 56% 31% 42%‡5.1% 10%

Kindle Fire HD 8.9” Android - - 22%‡11% 5.5%

Samsung Galaxy (7-8") Android 13% -

4.0% 5.1% 15% 19% 23%‡

2.9% 5.8%

Samsung Galaxy (>8) Android - 12%‡6.2% 3.1%

B&N NOOK HD/HD+ Android 1.9% - 0.6% 1.1% 17% 8.0% 0.9% -

Google Nexus 7 Android - - 2.3% 1.6% 14% 8.0% 1.2% -

Microsoft Surface Windows - - 0.5% 1.0% - 5.0% 0.6% -

Other - - - 5.8% 3.5% - 19% 2.8% -

* Usage share estimated based on distribution of all tablets by screen sizes (32% for 7-8”, 68% for 8.9-10.1”).

† Estimates normalized to 100% for iOS tablets only (16% for 7-8”, 59% for 8.9-10.1”).

‡ Estimates normalized to 100% for Android tablets only (16% for 7-8”, 8.6% for 8.9-10.1”).

Table B-8: Representative battery capacity and power draw estimates determined by a weighted average of the most 

popular tablet models.

Tablet Model Screen Size 

[inches]

Release

Year

Representative 

Weights

Battery 

Capacity*

[Wh]

Charger 

Efficiency 

[%]

Battery 

Recharge 

Time [hr]†

Power Draw [W]

Idle‡Unplugged§

iPad mini 1 7.9 2012 16% 16.5 75%a4.1 0.27a0.09

iPad 4 9.6 2012 15% 32.4 84% a5.1 0.14a0.08

iPad 3 9.6 2012 14% 43.0 81% a5.5 0.65a0.08e

iPad 2 9.6 2011-13 30% 25.0 81% a3.5 0.41a0.08

Kindle Fire HD 7” 7.0 2012 10% 16.5 75% e3.1 0.27e0.10

Kindle Fire HD 8.9” 8.9 2012 5.5% 22.2 81% e4.5 0.40e0.10

Galaxy Tab 3 7.0” 7.0 2013 5.8% 14.8 75% e3.6 e0.27e0.02

Galaxy Tab 3 10.1” 10.1 2012 3.1% 25.9 81% e5.0 0.40e0.09

Representative - - - 25.6 76% 4.2 0.27 0.08

* Battery capacity estimates from iFixit (2012-2013).

† Recharge time estimates from Tom’s Hardware (2012)

§ Average metered power draw from 10 measurements with a Yokogawa W210 power meter on Jan. 27, 2014.
150

a

Source: Apple environmental reports (Apple 2012).

e

No data for estimate, estimated based on mean of smaller (7-8”) and larger (≥8.9”) screens of iPad models.

Table B-9: Representative power draw estimate determined by the average of several aftermarket tablet chargers.

Charger Model Charger 

Efficiency [%]

Power Draw [W]

Unplugged Source

AmazonBasics Wall Charger (2.1A) - 0.16 Measurement

Trent NT90C 10W 5V/2A Dual USB Ports - 0.07 Measurement

Counterfeit iPad 66% 0.10 Shirriff 2012

KMS 69% 0.18 Shirriff 2012

Representative 68% 0.13 Average

Table B-10: Usage share of popular smartphone models used to derive weights, , to estimate the representative battery 

capacity and power draw values for smartphones.

Usage Base Share

Jan 14 Dec 13 Dec 13 Sep 13 May 13 Q2 2013

Aggregate

Representative 

Weights

 

Chitika 

2014

MixPanel 

2014a

StatCounter 

2013a

comScore 

2013

Magid 

2013

Nielsen 

Model OS 2013

iPhone 5S iOS - 13% 60% 41% 41% 40% 6.0% 9.4%

iPhone 5 iOS - 36% 16% 25%

iPhone 4S iOS - 27% 12% 19%

iPhone 4 iOS - 19% 8.7% 14%

iPhone 5C iOS - 4.5% 2.0% -

iPhone Other iOS - 1.8% 0.8% -

Samsung Galaxy S4 Android 24% - 16% 25% 26% 24% 5.4% 14%

Samsung Galaxy S3 Android 34% - 7.7% 20%

Samsung Galaxy S2 Android 8.4% - 1.9% -

Samsung Galaxy S Android 1.9% - 0.4% -

Samsung Galaxy Note 3 Android 3.8% - 0.9% -

Samsung Galaxy Note 2 Android 8.6% - 1.0% -

Samsung Galaxy Note Android 0.9% - 0.2% -

Samsung Galaxy Other Android 8.3% - 1.9% -

Samsung Other Android 10% - 2.4% -

HTC Android - - 2.8% 7.1% 9% 17% 6.7% -

Motorola Android - - 2.6% 6.8% 9% 10% 6.3% -

LG Android - - 3.1% 6.6% 7% 5.6% 6.4% -

RIM BlackBerry - - 3.6% - - 3.0% 5.3% -

Other - - - 12% 14% 11% 6.8% 9.9% -

Table B-11: Representative battery capacity and power draw estimates determined by a weighted estimate of the most 

popular smartphone models.

Smartphone Model Year 

Released

Representative 

Weights

Battery 

Capacity*

[Wh]

Charger 

Efficiency 

[%]

Battery 

Recharge 

Time [hr]†

Power Draw [W]

Idle Unplugged§

iPhone 5S 2013 9.4% 5.9 75%a- 0.09 0.02

iPhone 5 2012 25% 5.5 75%a1.8 0.71 0.21

iPhone 4S 2011 19% 5.3 75%a1.7 0.64 0.21

iPhone 4 2010 14% 5.3 75%a- 0.35 0.21

Samsung Galaxy S4 2013 14% 9.9 77% 2.9 0.43e0.02f

Samsung Galaxy S3 2012 20% 8.0 77% 2.5 0.43 0.01

Representative - - 6.5 76% 2.1 0.50 0.13

* Battery capacity estimates from iFixit (2012-2013).

† Recharge time estimates from Tom’s Hardware (2012).

§ Average metered power draw from 10 measurements with a Yokogawa W210 power meter on Jan. 27, 2014.
151

a

Source: Apple environmental reports (Apple 2012-2013).

e

No data for estimate, so assumed similar to Galaxy S3.

f

No data for estimate, but its charger is rated for 10W which is similar to tablets, so we assumed it is similar to the Samsung Galaxy Tab 3.

Table B-12: Representative power draw estimate determined by the average of several aftermarket smartphone chargers.

Charger Model Charger 

Efficiency [%]

Power Draw [W]

Source Unplugged

Kyocera SSW-2001 - 0.06 Measurement

Counterfeit iPhone 63% 0.38 Shirriff 2012

Monoprice 72% 0.08 Shirriff 2012

Belkin 66% 0.23 Shirriff 2012

Smartphone dataset 63% 0.11 DOE 2012

Representative 67% 0.19 Average

B.2.2.6 Whole Day Energy Consumption

The total energy consumption for the whole day is:

 

This estimate applies to the primary smartphones and primary tablets. However, we do not directly ask 

about charging behavior for secondary tablets. We estimate their energy consumption by assuming that 

the energy consumption between primary and secondary tablets follows the same ratio as usage time 

for the devices, i.e.:

 

  

 

 

 

where

 

 is the usage time per day for the primary tablet <M2b>

 

 is the usage time per day for the secondary tablet <M2c>

B.2.3 References

Apple. 2010. “iPhone 4 Environmental Report.” Jun. 24, 2010. 

http://www.apple.com/environment/reports/docs/iPhone_4_Product_Environmental_Report.pdf. 

Retrieved Oct. 9, 2013.

Apple. 2011. “iPhone 4S Environmental Report.” Oct. 4, 2011. 

http://images.apple.com/environment/reports/docs/iPhone4S_Product_Environmental_Report_201

1.pdf. Retrieved Oct. 9, 2013.

Apple. 2012a. “iPad 2 Environmental Report.” Mar. 7, 2012. 

http://images.apple.com/environment/reports/docs/iPad2_Product_Environmental_Report_2012.p

df. Retrieved Sept. 19, 2013.

Apple. 2012b. “iPad 3 Environmental Report.” Mar. 7, 2012. 

http://images.apple.com/environment/reports/docs/iPad_Product_Environmental_Report_March20

12.pdf. Retrieved Sept. 19, 2013.

Apple. 2012c. “iPad 4 Environmental Report.” Oct. 23, 2012. 

http://images.apple.com/environment/reports/docs/iPad_Retina_PER_oct2012.pdf. Retrieved Sept. 

19, 2013.
152

Apple. 2012d. “iPad mini Environmental Report.” Oct. 23, 2012. 

http://images.apple.com/environment/reports/docs/iPadmini_PER_oct2012.pdf. Retrieved Sept. 19, 

2013.

Apple. 2012e. “iPhone 5 Environmental Report.” Sept. 12, 2012. 

http://images.apple.com/environment/reports/docs/iPhone5_product_environmental_report_sept2

012.pdf. Retrieved Oct. 9, 2013.

Apple. 2013. “iPhone 5S Environmental Report.” Sept. 10, 2013. 

http://images.apple.com/environment/reports/docs/iPhone5s_product_environmental_report_sept

2013.pdf. Retrieved Oct. 9, 2013.

CEA. 2014. “Consumer Outlook on Tablets – Jan. 2014 Edition.” Jan. 2014. Consumer Electronics 

Association.

Chikita. 2013. “Third Quarter End Tablet Update: iPad Usage Share at 81%, Other Tablets See Share 

Increases.” Oct. 22, 2013. http://chitika.com/insights/2013/Q3-tablet-update. Retrieved Jan. 24, 

2014.

Chikita. 2014. “Samsung Status Report: Galaxy S III & IV Users Generate 57.7% of Samsung Smartphone 

Web Traffic in North America.” Jan. 14, 2014. http://chitika.com/insights/2014/samsung-update. 

Retrieved Jan. 17, 2014.

comScore. 2013b. “MobiLens Sep 2013 - Top Smartphone OEMs.” Nov. 5, 2013. 

http://www.comscore.com/Insights/Press_Releases/2013/11/comScore_Reports_September_2013_

U.S._Smartphone_Subscriber_Market_Share. Retrieved Jan. 22, 2014.

DOE. 2012. “Rulemaking for Battery Chargers and External Power Supplies Energy Conservation 

Standard. Energy Use Analysis Spreadsheet.” Feb. 17, 2012.

http://www.regulations.gov/#!documentDetail;D=EERE-2008-BT-STD-0005-0084. Retrieved Feb. 6, 

2014.

Fiksu. 2014. “iPad, iPhone, and iOS 7 Adoption Trackers.” Dec. 23, 2013. http://www.fiksu.com/iOS-7-

iPhone-5s-5c-Usage-Tracker#ipad-usage. Retrieved Jan. 21, 2014.

iFixit. 2010. “iPhone 4 Teardown.” http://www.ifixit.com/Teardown/iPhone+4+Teardown/3130/1.

Retrieved Oct. 23, 2013.

iFixit. 2011a. “iPad 2 Wi-Fi EMC 2415 Teardown.” http://www.ifixit.com/Teardown/iPad+2+WiFi+EMC+2415+Teardown/5071/2#s22967. Retrieved Oct. 4, 2013.

iFixit. 2011b. “iPhone 4S Teardown.” http://www.ifixit.com/Teardown/iPhone+4S+Teardown/6610/1.

Retrieved Oct. 23, 2013.

iFixit. 2012a. “iPad 3 4G Teardown.”

http://www.ifixit.com/Teardown/iPad+3+4G+Teardown/8277/3#s33152. Retrieved Oct. 4, 2013.

iFixit. 2012b. “iPad 4 Wi-Fi Teardown.” http://www.ifixit.com/Teardown/iPad+4+WiFi+Teardown/11462/1. Retrieved Oct. 4, 2013.

iFixit. 2012c. “iPad mini Wi-Fi Teardown.” http://www.ifixit.com/Teardown/iPad+mini+WiFi+Teardown/11423/2. Retrieved Oct. 4, 2013.

iFixit. 2012d. “iPhone 5 Teardown.” http://www.ifixit.com/Teardown/iPhone+5+Teardown/10525/2.

Retrieved Oct. 23, 2013.

iFixit. 2012e. “Kindle Fire HD Teardown.” Sept. 14, 2012.

http://www.ifixit.com/Teardown/Kindle+Fire+HD+Teardown/10457/1. Retrieved Oct. 4, 2013.

iFixit. 2012f. “Samsung Galaxy S3 Teardown.”

http://www.ifixit.com/Teardown/Samsung+Galaxy+S+III+Teardown/9391/1. Retrieved Oct. 23, 2013.
153

iFixit. 2012g. “Samsung Galaxy Tab 3 7.0 3G Teardown.”

http://www.ifixit.com/Teardown/Samsung+Galaxy+Tab+3+7.0+3G+Teardown/17357/2. Retrieved 

Oct. 4, 2013.

iFixit. 2013a. “iPhone 5S Teardown.” http://www.ifixit.com/Teardown/iPhone+5s+Teardown/17383/1.

Retrieved Oct. 21, 2013.

iFixit. 2013b. “Kindle Fire HD 8.9.” http://www.ifixit.com/Guide/Kindle+Fire+HD+8.9-

Inch+Battery+Replacement/12922. Retrieved Oct. 4, 2013.

iFixit. 2013c. “Samsung Galaxy S4 Teardown.”

http://www.ifixit.com/Teardown/Samsung+Galaxy+S4+Teardown/13947/1#s46407. Retrieved Oct. 

23, 2013.

iFixit. 2013d. “Samsung Galaxy Note 10.1 Teardown.”

http://www.ifixit.com/Teardown/Samsung+Galaxy+Note+10.1+Teardown/10144/2. Retrieved Oct. 4, 

2013.

Localytics. 2013. “Top Android Tablet Share (Global).” Nov. 7, 2013. 

http://www.localytics.com/blog/2013/fonblets-and-phablets-samsung-has-share-of-android-mobiledevices/. Retrieved Jan. 24, 2014.

Magid. 2013. “US Tablet Owners, by Model, 2013.” Jun. 19, 2013. 

http://www.emarketer.com/Article/With-More-Models-on-Market-How-Tablets-StackingUp/1009982. Retrieved Sept. 20, 2013.

MixPanel. 2014a. “iPhone Models.” Dec. 23, 2013. 

https://mixpanel.com/trends/#report/iphone_models. Retrieved Jan. 21, 2014.

MixPanel. 2014b. “Top tablets.” Dec. 23, 2013. 

https://mixpanel.com/trends/#report/top_tablets/from_date:-52,to_date:-30. Retrieved Jan. 21, 

2014.

Nielsen. 2013. “Who's Winning the U.S. Smartphone Market?” Aug. 6, 2013. 

http://www.nielsen.com/us/en/newswire/2013/whos-winning-the-u-s-smartphone-market-.html. 

Retrieved Oct. 22, 2013.

Shirriff. 2012. “A dozen USB chargers in the lab: Apple is very good, but not quite the best.” Oct. 27, 

2012. http://www.righto.com/2012/10/a-dozen-usb-chargers-in-lab-apple-is.html. Retrieved Oct. 7, 

2013.

StatCounter. 2013a. “Top Mobile Vendors in the United States.” Dec. 2013. 

http://gs.statcounter.com/#mobile_vendor-US-monthly-201309-201309-bar. Retrieved Jan. 17, 2014

StatCounter. 2013b. “Top Tablet Vendors in the United States.” Dec. 2013. 

http://gs.statcounter.com/#tablet-vendor-US-monthly-201304-201312. Jan. 24, 2014.
154

B.3 Video Game Consoles

B.3.1 Installed Base 

To estimate the installed base of video game consoles in the current study, we used the results from the 

CE Usage Survey (2013). In this survey we asked about the ownership of nine different video game 

consoles in U.S. households (see Appendix A.5 Q-E1). In the main body this study (see Section 3.13.1.1), 

we only presented the installed base of video game consoles available on the market before Jul. 2013. In 

this Appendix, we present an additional installed base estimate for Feb. 2014 that includes the recently 

released Sony PlayStation 4 and Microsoft Xbox One consoles (Figure B-1).

Figure B-1: Installed Base of video game consoles in Mar. 2014

B.3.2 Usage of video game consoles including 8th generation models 

Figure B-2 depicts our usage estimates for gaming consoles in Feb. 2014.

Figure B-2: Turned ON and actively used time of video game consoles

Figure B-3 presents the estimated breakdown of active-all time among different activities.

6.1

33

5.7

22

23

5.1

42

1.6

0 10 20 30 40 50

Xbox

Xbox 360

Xbox One

PS 2

PS 3

PS 4

Wii

Wii U

Microsoft Sony Nintendo

Millions

0

1

2

3

4

5

6

7

Xbox Wii U Xbox

One PS2 Xbox360 PS3 Wii PS4

Left ON 5.9 3.3 2.0 2.9 1.9 1.8 2.4 1.3

Actively used 0.5 1.1 1.5 0.6 1.5 1.5 0.5 0.5

Hours
155

Figure B-3: Distribution of active usage among gaming, video streaming and video playback by video game console platform

B.3.3 Power Draw

Table B-13 summarizes the power draw values for the PlayStation 4 (PS4), included estimated prelaunch power draw (Sony 2013) and measured power draws by NRDC (2013). With the exception of 

active-media and networked standby modes, these two sources are consistent. 

Table B-13: PS4 Power Draws (Sony 2013, NRDC 2013).

Mode Manufacturer

Power Draw [W]

NRDC (2013)

Power Draw [W]

Active-gaming 135a137

Active-media 110b90d

Navigation 85 88

Peripheral charging 10c-

Peripheral charging enabled 7 -

Networked standby 3.1 8.8

Standby <0.5 0.5

a Average measured while playing “Motorstorm Apocalypse.”

b Average of power used for playback of audio CD, DVD, Blu-ray, and media streaming.

c PS4 peripherals can be recharged while the console is powered-down.

d Power Draw measured while streaming Netflix.

Table B-14 presents the comparison of power draw data received from Microsoft (Calland 2014, middle 

column) with power measurements performed by NRDC (2013). The data from the two sources are 

mostly consistent, with the exception of the Standby power mode, where the measured power draw is 

almost three-times higher than the power draw provided by Microsoft.

Table B-14: Xbox One Power Draws (Calland 2014, NRDC 2013).

Mode Manufacturer

Power Draw [W]

NRDC (2013)

Power Draw [W]

Active-gaming 121 110

Active-video playback (DVD) 80 -

Active-video streaming 72 74

Navigation 72 72

Connected Standby 18a18

Standby 0.45a1.3

a Xbox One shipped with "Connected Standby " enabled -- wake-on-lan, wake-on-voice and 

instant-on (OS suspended to RAM). User can opt in to "energy saving" (0.5 watt) standby mode.

0%

20%

40%

60%

80%

100%

Xbox Xbox 360 Xbox

One

PS 2 PS 3 PS 4 Wii Wii U

Active-Video playback

Active-Video streaming

Active-Gaming
156

B.3.4 Usage estimates – Video Game Consoles

We reference specific survey questions to obtain values for variables in the usage model. These are 

indicated in bold green, e.g., <E1.1> references survey question 1, sub-question 01 in the video game 

console survey. See Appendix A – CE Usage Surveys for the survey questions. The following table 

includes the questions that we used in the energy model calculation (e.g. E3 – E5). 

Table B-15: Variables directly measured in the CE Usage Survey.

Survey Question Purpose Measure Variable

E3.## Turned ON and Active Usage time ... Active and ON time Time (hh:mm)

C2.01 Turned ON 

C2.02 Actively used 

E4.## Distribution of active usage time... Usage time Time (hh:mm)

C2.01 Play games 

C2.02 Stream media from the video game console or Internet 

C2.03 DVD and/or Blu-Ray playback 

E5.## Initial state of the Video Game Console in the morning... Left ON 24 hours Probability

C2011 It was already turned ON and ready to use 

C202 It was turned OFF and you needed to turn it on to use it 

C299 Don’t know  

 

B.3.4.1 Calculations of Time Spent in Operational Modes 

Video game consoles have three primary operational modes, i.e., active, navigation and standby. In our 

study, the active mode includes time spent gaming, streaming video, and video playback (see Video 

Game Systems 3.13). We declare these as variables in this model (see Table B-16). 

Table B-16: Variables for power draw and time threshold of various operational modes.

Operational Mode Activegaming

ActivestreamingActiveplayback Navigation Standby

Power Draw 

Time in modes 

In the CE Usage Survey (2013), we asked respondent to estimate the time each video game console was 

on “yesterday” and was used for gaming, streaming video, and video playback.

Not infrequently, the sum of times spent in the different active-use modes did not equal the active use 

estimate. Consequently, if is less than the sum of the time spent gaming, streaming, and 

video playback, we assumed that instead equaled that sum, i.e.:

 If then 

 .

Similarly, we then adjusted the on-mode time, , for each individual response if was less than 

 so that equals .
157

To determine whether or not a video game console stayed on all the time, we analyzed each individual 

response to survey question <E5>, i.e., whether or not the console was already on the last time the 

respondent was the first person to use the console on a day. Our data analysis logic follows, where the 

answer “-1” represents a “don’t know” reply by the respondent:

 If then and ;

 If 

 

 then and 

 , i.e. video game console was not used yesterday;

 If then and 

 , where “average time” is the weighted average time video game 

console was actively used yesterday and is calculated as described above;

 If then before adjustments and 

 before adjustments;

 If then ( ) and 

 .

The weighted average hours spent in on and active modes equals the sum of the individual responses, 

applying the appropriate survey weight, Nw, for each respondent:

 ∑

 

 

 

 

where

 is weight of the th survey response

 is number of survey responses

 is the number of a particular response

Finally, the time video game consoles spent in navigation mode was calculated as the difference 

between the time spent in on mode and the time video game consoles were actively used, i.e.,

 .

B.3.5 References

Calland, T. 2014. Personal Communication. Microsoft. Feb.

Sony. 2013. Personal Communication. Dec.

NRDC. 2013. “New PS4 and Xbox One Game Consoles: A Mixed Bag for Energy Efficiency.” Switchboard. 

Dec. http://switchboard.nrdc.org/blogs/nhorowitz/new_ps4_and_xbox_one_game_cons.html
158

B.4 Home Audio

In this appendix, we present in-store power measurements of speaker docks and stereo shelf systems 

performed in Jan. 2014. 

B.4.1 Speaker Docks

Table B-17: Power draw measurements of speaker docks.

Active Modes [W]

Active iPhone Active Tuner Active Standby Off

Min. Medium Max. Min. Medium Max. [W] [W]

Stereo System 1*5.6 5.4 6.6 4.1 6.3 3.3 1.9 5.6

Stereo System 2** 3.3 4.5 7.8 - - 1.9 0.4 3.3

Stereo System 3#- - - - - - 1.1 -

Wt. Avg. 5.0 5.2 6.9 4.1 6.3 3.0 1.3 5.0

Wt. Avg. 4.8 3.0 1.3

* This speaker dock has a plug-in connection for an iPhone 5. Since we did not have an iPhone 5 available when making the 

measurements, we were unable to measure power draw in active modes.

B.4.2 Shelf Stereo Systems

Table B-18: Power draw measurements of shelf stereo systems.

Active Modes [W]

Active iPhone Active Tuner Active Standby Off

Min. Medium Max. Min. Medium Max. [W] [W]

Stereo System 1*14 15 28 12 14 40 13 0.3

Stereo System 2** 12 13 52 12 15 70 10 0.1

Stereo System 3#18 19 28 18 18 53 13 0.5

Wt. Avg. 15 16 34 14 15 51 12 0.3

Wt. Avg. 17 12 0.3

* Output power = 220W.

** Output power = 500W.

# Output power = 700W.